Exploring immune interactions in triple negative breast cancer: IL-1β inhibition and its therapeutic potential
Bibliographic record
Abstract
Triple negative breast cancer (TNBC) has poor prognosis when compared to other breast cancer subtypes. Despite pre-clinical data supporting an immune targeted approach for TNBCs, immunotherapy has failed to demonstrate the impressive responses seen in other solid tumor malignancies. Additional strategies to modify the tumor immune microenvironment and potentiate response to immunotherapy are needed. In this review, we summarise phase III data supporting the use of immunotherapy for TNBC. We discuss the role of IL-1β in tumorigenesis and summarize pre-clinical data supporting IL-1β inhibition as a potential therapeutic strategy in TNBC. Finally, we present current trials evaluating IL-1β in breast cancer and other solid tumor malignancies and discuss future studies that may provide a strong scientific rationale for the combination of IL-1β and immunotherapy in the neoadjuvant and metastatic setting for people with TNBC.
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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 | 0.001 | 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 | 0.001 |
| 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".