Tumors produce glucocorticoids by metabolite recycling, not synthesis, and activate Tregs to promote growth
Bibliographic record
Abstract
Glucocorticoids are steroid hormones with potent immunosuppressive properties. Their primary source is the adrenals, where they are generated via de novo synthesis from cholesterol. In addition, many tissues have a recycling pathway in which glucocorticoids are regenerated from inactive metabolites by the enzyme 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1, encoded by Hsd11b1). Here, we find that multiple tumor types express Hsd11b1 and produce active glucocorticoids. Genetic ablation of Hsd11b1 in such cells had no effect on in vitro growth, but reduced in vivo tumor progression, which corresponded with increased frequencies of CD8+ tumor-infiltrating lymphocytes (TILs) expressing activation markers and producing effector cytokines. Tumor-derived glucocorticoids were found to promote signatures of Treg activation and suppress signatures of conventional T cell activation in tumor-infiltrating Tregs. Indeed, CD8+ T cell activation was restored and tumor growth reduced in mice with Treg-specific glucocorticoid receptor deficiency. Importantly, pharmacologic inhibition of 11β-HSD1 reduced tumor growth to the same degree as gene knockout and rendered immunotherapy-resistant tumors susceptible to PD-1 blockade. Given that HSD11B1 expression is upregulated in many human tumors and that inhibition of 11β-HSD1 is well tolerated in clinical studies, these data suggest that targeting 11β-HSD1 may be a beneficial adjunct in cancer therapy.
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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".