Overexpression of the human tissue kallikrein genes KLK4, 5, 6, and 7 increases the malignant phenotype of ovarian cancer cells
Bibliographic record
Abstract
The human tissue kallikrein family of serine proteases (hK1-hK15 encoded by the genes KLK1-KLK15) is involved in several cancer-related processes. Accumulating evidence suggests that certain tissue kallikreins are part of an enzymatic cascade pathway that is activated in ovarian cancer and other malignant diseases. In the present study, OV-MZ-6 ovarian cancer cells were stably co-transfected with plasmids expressing hK4, hK5, hK6, and hK7. These cells displayed similar proliferative capacity as the vector-transfected control cells (which do not express any of the four tissue kallikreins), but showed significantly increased invasive behavior in an in vitro Matrigel invasion assay (p<0.01; Mann-Whitney U-test). For in vivo analysis, the cancer cells were inoculated into the peritoneum of nude mice. Simultaneous expression of hK4, hK5, hK6, and hK7 resulted in a remarkable 92% mean increase in tumor burden compared to the vector-control cell line. Five out of 14 mice in the 'tissue kallikrein overexpressing' group displayed a tumor/situs ratio greater than 0.198, while this weight limit was not exceeded at all in the vector control group consisting of 13 mice (p=0.017; chi2 test). Our results strongly support the view that tumor-associated overexpression of tissue kallikreins contributes to ovarian cancer progression.
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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 | 0.000 |
| 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".