High kallikrein‐related peptidase 6 in non‐small cell lung cancer cells: an indicator of tumour proliferation and poor prognosis
Bibliographic record
Abstract
The human kallikrein-related peptidases (KLK) are serine proteases whose concentrations are often abnormal in common human malignancies and contribute to neoplastic progression through multifaceted roles. However, little attention has been paid to their synthesis and involvement in the development and dissemination of lung cancer, the leading cause of cancer mortality worldwide. We have analysed the production of KLK6 in normal lung and tumour tissues from patients with non-small cell lung cancer (NSCLC). KLK6 immunoreactivity was restricted to epithelial cells of the normal bronchi, but most of the cancer samples were moderately or highly immunoreactive, regardless of the histological subtype. In contrast, little or no KLK6 was detected in NSCLC cells. We have developed NSCLC lines expressing wild-type KLK6 in order to investigate the role of KLK6 in lung cancer biology, and analysed its impact on proliferation. Ectopic KLK6 dramatically enhanced NSCLC cell growth and KLK6-producing NSCLC cells had accelerated cell cycles, between the G1 and S phases. This was accompanied by a marked increase in cyclin E and decrease in p21. KLK6 production was also associated with enhanced synthesis of c-Myc, which is known to promote cell-cycle progression. Finally, examination of specimens from patients with NSCLC revealed that KLK6 mRNA is overexpressed in tumour tissue, and high KLK6 concentrations were associated with lower survival rates. We conclude that a high concentration of KLK6 is an indicator of tumour proliferation and an independent predictive factor in NSCLC.
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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 | 0.000 | 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".