The prognostic and predictive value of Tregs and tumor immune subtypes in postmenopausal, hormone receptor-positive breast cancer patients treated with adjuvant endocrine therapy: a Dutch TEAM study analysis
Bibliographic record
Abstract
Evidence exists for an immunomodulatory effect of endocrine therapy in hormone receptor-positive (HR+ve) breast cancer (BC). Therefore, the aim of this study was to define the prognostic and predictive value of tumor immune markers and the tumor immune profile in HR+ve BC, treated with different endocrine treatment regimens. 2,596 Dutch TEAM patients were treated with 5 years of adjuvant hormonal treatment, randomly assigned to different regimens: 5 years of exemestane or sequential treatment (2.5 years of tamoxifen-2.5 years of exemestane). Immunohistochemistry was performed for HLA class I, HLA-E, HLA-G, and FoxP3. Tumor immune subtypes (IS) (low, intermediate & high immune susceptible) were determined by the effect size of mono-immune markers on relapse rate. Patients on sequential treatment with high level of tumor-infiltrating FoxP3+ cells had significant (p = 0.019, HR 0.729, 95% CI 0.560-0.949) better OS. Significant interaction for endocrine treatment and FoxP3+ presence was seen (OS p < 0.001). Tumor IS were only of prognostic value for the sequentially endocrine-treated patients (RFP: p = 0.035, HR intermediate IS 1.420, 95% CI 0.878-2.297; HR low IS 1.657, 95% CI 1.131-2.428; BCSS: p = 0.002, HR intermediate IS 2.486, 95% CI 1.375-4.495; HR low IS 2.422, 95% CI 1.439-4.076; and OS: p = 0.005, HR intermediate IS 1.509, 95% CI 0.950-2.395; HR low IS 1.848, 95% CI 1.277-2.675). Tregs and the tumor IS presented in this study harbor prognostic value for sequentially endocrine-treated HR+ve postmenopausal BC patients, but not for solely exemestane-treated patients. Therefore, these markers could be used as a clinical risk stratification tool to guide adjuvant treatment in this BC population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".