Tumour-infiltrating FOXP3+ lymphocytes are associated with cytotoxic immune responses and good clinical outcome in oestrogen receptor-negative breast cancer
Bibliographic record
Abstract
BACKGROUND: Regulatory T cells (Tregs) are commonly identified by expression of the transcription factor FOXP3 and are conventionally thought to promote cancer progression by suppressing anti-tumour immune responses. We examined the relationship between FOXP3(+) tumour-infiltrating lymphocytes (TIL) and prognosis in oestrogen receptor (ER)-negative breast cancer, a tumour subtype with poor clinical outcome in which TIL are abundant. METHODS: FOXP3(+) and CD8(+) TIL were assessed by immunohistochemistry in a cohort of 175 ER- breast tumours. Results were confirmed in an independent data set of 78 ER- breast tumours with publically available gene expression data. RESULTS: High FOXP3(+) TIL levels were strongly associated with prolonged recurrence-free survival (HR=0.461, P=0.0002), particularly among basal-like tumours (HR=0.280, P=0.0001), for which FOXP3 status was independent of standard prognostic factors. Over 75% of FOXP3(+) TIL in triple negative breast tumours displayed a conventional CD4(+)CD25(+) Treg phenotype. Importantly, FOXP3(+) TIL were positively correlated with CD8(+) (cytotoxic) T cells (r(s)=0.76, P<0.0001), and were prognostically insignificant in tumours with low levels of CD8(+) TIL. These observations were confirmed in an independent cohort. CONCLUSION: In contrast with current dogma, we show for the first time that FOXP3(+) TIL are associated with robust anti-tumour immunity and favourable prognosis in ER- 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".