Functional proteomics of kallikrein-related peptidases in ovarian cancer ascites fluid
Bibliographic record
Abstract
Kallikrein-related peptidases (KLKs) are secreted serine proteinases with trypsin or chymotrypsin-like activity. Several family members, such as KLKs 6 and 10, are potential ovarian cancer biomarkers. Recently, using a newly developed assay for active KLK6, we found that only a very small proportion of immunoreactive KLK6 in tumor-derived clinical samples (malignant ascites fluid), in cerebrospinal fluid, and in cancer cell line supernatants is enzymatically active. We therefore hypothesized that a proportion of other immunoreactive KLKs in such samples could be present, but might be partly complexed to endogenous serine proteinase inhibitors. Using a combination of immunological isolation of the enzymes, activity-based probe analysis and proteomics, we identified active KLK10 in ovarian cancer ascites and we provide preliminary data that the activity of other KLKs present in these samples can be decreased by known proteinase inhibitors (e.g., alpha2-macroglobulin, alpha1-antitrypsin). Our data suggest that the enzymatic activity of ovarian cancer-released KLKs that are detected by regular immunoassays is low in vivo and very likely regulated by proteinase inhibitors.
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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 | 0.001 | 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) | 0.001 | 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".