MAIT cells promote cancer progression and regulatory T cell accumulation in bladder tumor microenvironment
Bibliographic record
Abstract
Background Mucosa-associated invariant T (MAIT) cells represent a unique population of innate-like T lymphocytes capable of detecting non-peptide antigens in the context of monomorphic antigen-presenting molecules. Due to their abundance in barrier tissues, reactivity to local inflammatory cues, and cytotoxic and regulatory functions, MAIT cells are poised to shape the dynamics of various tumor microenvironments. Growing evidence suggests that MAIT cells can exert protumor and/or antitumor effects in cancers arising from or metastasizing to mucosal tissues. However, MAIT cell roles in bladder cancer (BCa) remains unclear. Methods To begin to identify MAIT cells in BCa, we stained bladder tumor biopsies for T cell receptor (TCR) Vα7.2 + cells. We then refined a human MAIT cell signature, which enabled us to interrogate a bulk RNA sequencing dataset and conduct correlation analyses linking intratumoral MAIT cell abundance and mortality from BCa. To extend our work to an in vivo setting, we employed a clinically relevant mouse model in which Mr1 +/+ B6-MAIT CAST (MAIT-sufficient) and Mr1 −/− B6-MAIT CAST (MAIT-deficient) mice were exposed to N-butyl-N-(4-hydroxybutyl)nitrosamine, a chemical carcinogen associated with tobacco smoke. In additional experiments, MAIT cells were functionally removed through acetyl-6-formylpterin (Ac-6-FP) administration. Effector and regulatory cell types were phenotyped by flow cytometry, and BCa tumor burden and progression were assessed by MRI and/or H&E and Ki67 staining. Results TCR Vα7.2 + cells were readily detectable in several BCa biopsies, and our bioinformatic analyses correlated heavier MAIT cell presence in BCa tumors with poorer overall survival. Similarly, we found higher tumor burdens in Mr1 +/+ B6-MAIT CAST mice than in Mr1 −/− or Ac-6-FP-treated animals. Bladder MAIT cells from tumor-bearing mice exhibited phenotypic MAIT17 bias based on transcription factors they harbored along with increased interleukin-17A and tumor necrosis factor-α production capacities upon stimulation. Finally, FoxP3 + regulatory T (T reg ) cell frequencies were elevated in Mr1 +/+ mouse bladder tumors, likely contributing to an immunosuppressive tumor microenvironment, a finding that could be recapitulated in our transcriptomic studies on human BCa. Conclusions MAIT cells are abundant in BCa tumor microenvironments where they potentiate T reg cell accumulation and play protumor roles.
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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".