Disease processes may be reflected by correlations among tissue kallikrein proteases but not with proteolytic factors uPA and PAI-1 in primary ovarian carcinoma
Bibliographic record
Abstract
In epithelial ovarian cancer, the high mortality rate is usually ascribed to late diagnosis, since these tumors commonly lack early-warning symptoms, but tumor-associated biomarkers useful for prognosis or therapy response prediction are in short supply. However, members of the tissue kallikrein serine protease family, the serine protease uPA and its inhibitor PAI-1, are associated with tumor progression of ovarian cancer. Therefore, we used ELISA to determine uPA, PAI-1, and tissue kallikreins hK5-8, 10, 11, and 13 in extracts of 142 primary tumor tissue specimens from ovarian cancer patients and studied the strength of association between protein expression levels of these tumor tissue-associated factors. uPA, PAI-1, hk5, and hk8 were related to FIGO stage; hK5 expression was higher in FIGO III/IV than in FIGO I/II patient tissues. PAI-1 and hk5 differed significantly according to nuclear grading; expression of hK5 was higher in G3 than in G1/2 tumors. Associations between uPA, PAI-1, and the tissue kallikreins were weak. There were strong pairwise correlations within the cluster of tissue kallikreins hK5, 6, 7, 8, 10, and 11, but their bivariate distributions depended on nuclear grading. These results support the notion that several tissue kallikreins are co-expressed in ovarian cancer patients, substantiating the existence of a steroid hormone-driven tissue kallikrein cascade in this disease.
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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) | 0.000 | 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".