Inflammation and breast cancer. Metalloproteinases as common effectors of inflammation and extracellular matrix breakdown in breast cancer
Bibliographic record
Abstract
Two rapidly evolving fields are converging to impact breast cancer: one has identified novel substrates of metalloproteinases that alter immune cell function, and the other has revealed a role for inflammation in human cancers. Evidence now shows that the mechanisms underlying these two fields interact in the context of breast cancer, providing new opportunities to understand this disease and uncover novel therapeutic strategies. The metalloproteinase class of enzymes is well studied in mammary gland development and physiology, but mostly in the context of extracellular matrix modification. Aberrant metalloproteinase expression has also been implicated in breast cancer progression, where these genes act as tumor modifiers. Here, we review how the metalloproteinase axis impacts mammary physiology and tumorigenesis and is associated with inflammatory cell influx in human breast cancer, and evaluate its potential as a regulator of inflammation in the mammary gland.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".