Study of kallikrein-related peptidase 6 (KLK6) and its complex with α1-antitrypsin in biological fluids
Bibliographic record
Abstract
BACKGROUND: Human kallikrein-related peptidase 6 (KLK6) is a member of the kallikrein family of serine proteases. KLK6 is synthesized as a preproenzyme, mainly in tissues of the central nervous system (CNS), and secreted as an inactive precursor. Serum KLK6 is a biomarker of unfavorable prognosis for ovarian cancer, but its sensitivity for early detection is relatively low. Differential glycosylation of KLK6 has been identified in ascites fluid obtained from ovarian cancer patients, suggesting the presence of unique KLK6 isoforms in biological samples. METHODS: In the present study, we applied a two-step enrichment approach for KLK6 in ovarian cancer ascites, followed by mice immunization and production of monoclonal antibodies. Immunoaffinity techniques coupled to mass spectrometric methods were employed for hybridoma screening and target antigen identification. RESULTS: We found that the main target of the newly-generated monoclonal antibodies target was the serine protease inhibitor α1-antitrypsin (A1AT). Additional experiments confirmed that A1AT is the main inhibitor of KLK6 in biological fluids. One new antibody (24ED138) was chosen to build a hybrid assay for the accurate quantification of the A1AT-KLK6 complex in biological samples. The aforementioned assay was evaluated with serum samples collected from patients with ovarian cancer (n=24) and normal donors (n=16) and showed slight improvement in sensitivity (~12%) compared to the standard in-house KLK6 assay. CONCLUSIONS: We conclude that KLK6 is present in biological fluids either as free form, or bound to A1AT, and the bound form performs better than total KLK6 as a biomarker of ovarian carcinoma.
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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".