CCR5+ regulatory T cells induced by metastatic breast carcinomas migrate toward a gradient of CCL8 and accumulate in metastatic lung tissue (TUM9P.1016)
Bibliographic record
Abstract
Abstract Under homeostatic conditions, regulatory T cells (Tregs) mediate peripheral tolerance and prevent autoimmunity. Despite their crucial role in the regulation of immunity toward innocuous antigens, Tregs may also contribute to the growth and metastasis of breast cancer by suppressing anti-tumor immune responses. We are interested in developing therapies to inhibit intratumoral Treg infiltration to decrease the growth of primary and metastatic tumors. Using mammary carcinomas syngenic to BALB/c mice, we identified elevated levels of CCR5+Tregs in the primary tumour and metastatic lungs relative to naive control tissues. Interestingly, we observed that C-C chemokine receptor type 5 (CCR5) is highly and selectively expressed by Tregs in metastatic lungs relative to other immune cell populations. CCR5+Tregs largely co-express CTLA-4 and CD103, indicating a suppressive phenotype. The production of CCL8, an endogenous ligand of CCR5, was increased in the tumour and lungs, and CCL8-mediated migration of Tregs ex vivo was inhibited by the CCR5 antagonist Maraviroc. These data suggest that targeting CCR5 or CCL8 may be a viable therapeutic strategy to inhibit Treg accumulation during tumour progression to decrease metastatic tumour growth. Currently, there is a paucity of research involving the role of CCR5+Tregs in tumour progression. We anticipate that this work will advance the generation of targeted, immune-based therapeutics for the treatment of metastatic breast cancer.
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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) | 0.004 | 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".