Tremelimumab in Combination with Exemestane in Patients with Advanced Breast Cancer and Treatment-Associated Modulation of Inducible Costimulator Expression on Patient T Cells
Bibliographic record
Abstract
PURPOSE: Tremelimumab is a fully human monoclonal antibody specific for CTL-associated antigen 4 (CTLA4) with single-agent activity in certain tumors but has not been evaluated in patients with breast cancer. EXPERIMENTAL DESIGN: In a phase 1 study, 26 patients with advanced, hormone-responsive breast cancer received tremelimumab (3-10 mg/kg) every 28 days or every 90 days plus exemestane 25 mg daily. The objectives were to determine safety and the maximum tolerated dose (MTD) of tremelimumab with exemestane and, secondarily, to assess tumor response, pharmacokinetics, and immune pharmacodynamics. RESULTS: Most treatment-related adverse events were mild to moderate with the most common being diarrhea (46% of patients), pruritus (42%), constipation (23%), and fatigue (23%). Dose-limiting toxicities were transient serum transaminase elevations (one patient) and diarrhea (four patients). The MTD of tremelimumab with exemestane was 6 mg/kg every 90 days. Among 13 patients treated at the MTD, none developed grade 3 or 4 treatment-related diarrhea. No pharmacokinetic interaction was observed between tremelimumab and exemestane. The best overall response was stable disease for >or=12 weeks in 11 patients (42%). Treatment was associated in most patients with increased peripheral CD4+ and CD8+ T cells expressing inducible costimulator (ICOS) and a marked increase in the ratio of ICOS+ T cells to FoxP3+ regulatory T cells. CONCLUSIONS: Tremelimumab plus exemestane is tolerable in patients with hormone-responsive advanced breast cancer. Treatment is associated with increased ICOS+ T cells, which likely signals immune activation secondary to CTL-associated antigen 4 blockade.
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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) | 0.001 | 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".