Proteolysis of cystatin C by cathepsin D in the breast cancer microenvironment
Bibliographic record
Abstract
The aspartic protease cathepsin D, a poor prognostic indicator of breast cancer, is abundantly secreted as procathepsin D by human breast cancer cells and self‐activates at low pH in vitro , giving rise to catalytically active cathepsin D. Due to a lower extracellular pH in tumor microenvironments compared to normal tissues, cathepsin D may cleave pathophysiological substrates contributing to cancer progression. Here, we show by yeast 2‐hybrid and degradomics analyses that cystatin C, the most potent natural secreted inhibitor of cysteine cathepsins, both binds to and is a substrate of extracellular procathepsin D. The amount of cystatin C in the extracellular environment is reduced in the secretome of mouse embryonic fibroblasts stably transfected with human cathepsin D. Cathepsin D extensively cleaved cystatin C in vitro at low pH. Cathepsin D secreted by breast cancer cells also processed cystatin C at the pericellular pH of tumors and so enhancing extracellular proteolytic activity of cysteine cathepsins. Thus, tumor derived cathepsin D assists breast cancer progression by reducing cystatin C activity, which, in turn, enhances cysteine cathepsin proteolytic activity, revealing a new link between protease classes in the protease web.—Laurent‐Matha, V., Huesgen, P. F., Masson, O., Derocq, D., Prébois, C., Gary‐Bobo, M., Lecaille, F., Rebière, B., Meurice, G., Oréar, C., Hollingsworth, R. E., Abrahamson, M., Lalmanach, G., Overall, C. M., Liaudet‐Coopman, E. Proteolysis of cystatin C by cathepsin D in the breast cancer microenvironment. FASEB J. 26, 5172–5181 (2012). www.fasebj.org
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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 | 0.001 | 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 | 0.000 |
| 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".