Maraviroc decreases CCL8-mediated migration of CCR5<sup>+</sup>regulatory T cells and reduces metastatic tumor growth in the lungs
Bibliographic record
Abstract
Regulatory T cells (Tregs) play a crucial physiological role in the regulation of immune homeostasis, although recent data suggest Tregs can contribute to primary tumor growth by suppressing antitumor immune responses. Tregs may also influence the development of tumor metastases, although there is a paucity of information regarding the phenotype and function of Tregs in metastatic target organs. Herein, we demonstrate that orthotopically implanted metastatic mammary tumors induce significant Treg accumulation in the lungs, which is a site of mammary tumor metastasis. Tregs in the primary tumor and metastatic lungs express high levels of C-C chemokine receptor type 5 (CCR5) relative to Tregs in the mammary fat pad and lungs of tumor-free mice, and Tregs in the metastatic lungs are enriched for CCR5 expression in comparison to other immune cell populations. We also identify that C-C chemokine ligand 8 (CCL8), an endogenous ligand of CCR5, is produced by F4/80(+) macrophages in the lungs of mice with metastatic primary tumors. Migration of Tregs toward CCL8 ex vivo is reduced in the presence of the CCR5 inhibitor Maraviroc. Importantly, treatment of mice with Maraviroc (MVC) reduces the level of CCR5(+) Tregs and metastatic tumor burden in the lungs. This work provides evidence of a CCL8/CCR5 signaling axis driving Treg recruitment to the lungs of mice bearing metastatic primary tumors, representing a potential therapeutic target to decrease Treg accumulation and metastatic tumor growth.
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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".