CD25 Identifies a Subset of CD4+FoxP3− TIL That Are Exhausted Yet Prognostically Favorable in Human Ovarian Cancer
Bibliographic record
Abstract
CD25, the alpha subunit of the IL2 receptor, is a canonical marker of regulatory T cells (Treg) and hence has been implicated in immune suppression in cancer. However, CD25 is also required for optimal expansion and activity of effector T cells in peripheral tissues. Thus, we hypothesized that CD25, in addition to demarcating Tregs, might identify effector T cells in cancer. To investigate this possibility, we used multiparameter flow cytometry and IHC to analyze tumor-infiltrating lymphocytes (TIL) in primary high-grade serous carcinomas, the most common and fatal subtype of ovarian cancer. CD25 was expressed primarily by CD4⁺ TIL, with negligible expression by CD8⁺ TIL. In addition to conventional CD25⁺FoxP3⁺ Tregs, we identified a subset of CD25⁺FoxP3⁻ T cells that comprised up to 13% of CD4⁺ TIL. In tumors with CD8⁺ TIL, CD25⁺FoxP3⁻ T cells showed a strong positive association with patient survival (HR, 0.56; P = 0.02), which exceeded the negative effect of Tregs (HR, 1.55; P = 0.09). Among CD4⁺ TIL subsets, CD25⁺FoxP3⁻ cells expressed the highest levels of PD-1. Moreover, after in vitro stimulation, they failed to produce common T-helper cytokines (IFNγ, TNFα, IL2, IL4, IL10, or IL17A), suggesting that they were functionally exhausted. In contrast, the more abundant CD25⁻FoxP3⁻ subset of CD4⁺ TIL expressed low levels of PD-1 and produced T-helper 1 cytokines, yet conferred no prognostic benefit. Thus, CD25 identifies a subset of CD4⁺FoxP3⁻ TIL that, despite being exhausted at diagnosis, have a strong, positive association with patient survival and warrant consideration as effector T cells for immunotherapy.
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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 | 0.001 | 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 | 0.000 |
| 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".