Inhibition of cathepsin B activity attenuates extracellular matrix degradation and inflammatory breast cancer invasion
Bibliographic record
Abstract
INTRODUCTION: Inflammatory breast cancer (IBC) is an aggressive, metastatic and highly angiogenic form of locally advanced breast cancer with a relatively poor three-year survival rate. Breast cancer invasion has been linked to proteolytic activity at the tumor cell surface. Here we explored a role for active cathepsin B on the cell surface in the invasiveness of IBC. METHODS: We examined expression of the cysteine protease cathepsin B and the serine protease urokinase plasminogen activator (uPA), its receptor uPAR and caveolin-1 in two IBC cell lines: SUM149 and SUM190. We utilized a live cell proteolysis assay to localize in real time the degradation of type IV collagen by IBC cells. IBC patient biopsies were examined for expression of cathepsin B and caveolin-1. RESULTS: Both cell lines expressed comparable levels of cathepsin B and uPA. In contrast, levels of caveolin-1 and uPAR were greater in SUM149 cells. We observed that uPA, uPAR and enzymatically active cathepsin B were colocalized in caveolae fractions isolated from SUM149 cells. Using a live-cell proteolysis assay, we demonstrated that both IBC cell lines degrade type IV collagen. The SUM149 cells exhibit predominantly pericellular proteolysis, consistent with localization of proteolytic pathway constitutents to caveolar membrane microdomains. A functional role for cathepsin B was confirmed by the ability of CA074, a cell impermeable and highly selective cathepsin B inhibitor, to significantly reduce pericellular proteolysis and invasion by SUM149 cells. A statistically significant co-expression of cathepsin B and caveolin-1 was found in IBC patient biopsies, thus validating our in vitro data. CONCLUSION: Our study is the first to show that the proteolytic activity of cathepsin B and its co-expression with caveolin-1 contributes to the aggressiveness of IBC.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.002 | 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".