Expression analysis of the human kallikrein 7 (KLK7) in breast tumors: a new potential biomarker for prognosis of breast carcinoma
Bibliographic record
Abstract
Kallikreins are a subgroup of serine proteases that are involved in the post-translational processing of polypeptide precursors. Growing evidence suggests that many kallikreins are implicated in carcinogenesis. Human kallikrein gene 7 (KLK7; HSCCE) is a new member of the human kallikrein gene family. KLK7 is expressed in normal breast tissue and is up-regulated in breast cancer cells by estrogens and glucocorticoids. In the present study, expression of the KLK7 gene in 92 breast cancer tissues was analyzed by reverse transcription-PCR (RT-PCR) and direct sequencing of several samples. The results were correlated with other clinicopathological variables and patient outcome. KLK7 gene expression was significantly lower in breast cancer patients of low stage (I/II) (p = 0.011) and patients with positive progesterone receptors (p = 0.022). Survival analysis showed that breast cancer patients with KLK7 positive tumors have relatively shorter disease-free survival (DFS) and overall survival (OS) than patients with KLK7 negative tumors. These data suggest that KLK7 gene expression may be used as a marker of unfavorable prognosis for breast cancer patients.
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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 | 0.000 |
| 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".