Human Kallikrein 13 Protein in Ovarian Cancer Cytosols: A New Favorable Prognostic Marker
Bibliographic record
Abstract
PURPOSE: Human kallikrein 13 (hK13; encoded by the KLK13 gene) is a secreted serine protease expressed in endocrine tissues, including the prostate, testis, breast, and ovary. We have previously reported steroid hormone regulation of the KLK13 gene and its clinical value as a marker of favorable prognosis in breast cancer at the mRNA level. We hypothesized that hK13 may represent a potential biomarker for ovarian carcinomas. PATIENTS AND METHODS: Using a newly developed enzyme-linked immunosorbent assay (ELISA), hK13 levels were quantified in 131 ovarian tumor extracts and correlated with various clinicopathological variables and outcome (progression-free survival [PFS], overall survival [OS]), over a median follow-up period of 42 months. RESULTS: hK13 concentration in ovarian tumor cytosols ranged from 0 to 18.4 ng/mg of total protein. An optimal cutoff value of 0.13 ng/mg (67(th) percentile) was selected, based on the ability of hK13 values to predict the PFS of the study population, to categorize tumors as hK13-positive or negative. Women with hK13-positive tumors most often had early stage (stage I/II) disease, no residual tumor after surgery and optimal debulking success (P <.05). Univariate and multivariate Cox regression analyses revealed that patients with hK13-positive tumors had a significantly longer PFS and OS than hK13-negative patients (P <.05). Kaplan-Meier survival curves further confirmed a reduced risk of relapse and death in women with hK13-positive tumors (P =.007 and P =.002, respectively). CONCLUSION: These results indicate that hK13 is an independent marker of favorable prognosis in ovarian cancer.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 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".