Human kallikrein 11: a new biomarker of prostate and ovarian carcinoma.
Bibliographic record
Abstract
Human kallikrein 11 (hK11) is a putative serine protease of the human kallikrein gene family. Currently, no methods are available for measuring hK11 in biological fluids and tissues. Our aim was to develop immunological reagents and assays for measuring hK11 and examine if the concentration of this kallikrein is altered in disease states. We produced recombinant hK11 protein in a baculovirus system and used it to develop monoclonal and polyclonal antibodies against hK11. We then developed an immunofluorometric procedure for measuring hK11 in biological fluids and tissue extracts with high sensitivity and specificity. We further quantified hK11 in various biological fluids and in serum of patients with various cancers. The hK11 immunofluorometric assay is highly sensitive (detection limit, 0.1 microg/l) and specific (no detectable cross-reactivity for other homologous kallikreins). We established the tissue expression pattern of hK11 at the protein level and found the highest levels in the prostate, followed by stomach, trachea, skin, and colon. We have immunohistochemically localized hK11 in epithelial cells of various organs. We further detected hK11 in amniotic fluid, milk of lactating women, cerebrospinal fluid, follicular fluid, and breast cancer cytosols. However, highest levels were seen in prostatic tissue extracts and seminal plasma. hK11 in seminal plasma and prostatic extracts is present at approximately 300-fold lower levels than prostate-specific antigen and at approximately the same levels as hK2. hK11 expression in breast cancer cell lines is up-regulated by estradiol. Elevated serum levels of hK11 were found in 70% of women with ovarian cancer and in 60% of men with prostate cancer. This is the first reported immunological assay for hK11. Analysis of this biomarker in serum may aid in the diagnosis and monitoring of ovarian and prostatic 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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".