Amplification of telomerase (hTERT) gene is a poor prognostic marker in non-small-cell lung cancer
Bibliographic record
Abstract
Telomerase reactivation is a hallmark of human carcinogenesis. Increased telomerase activity may result from gene amplification and/or overexpression. This study evaluates the prognostic value of hTERT gene amplification and mRNA overexpression in 144 resectable non-small-cell lung cancer (NSCLC) specimens. The hTERT gene copy number was assessed by quantitative polymerase chain reaction (qPCR) on laser-capture microdissected tumour cells of 81 tumours, and by fluorescence in situ hybridisation (FISH) on a subset of 59 tumours. hTERT mRNA level was determined by reverse transcription (RT)-qPCR in 130 tumours. In total, 57% of (46 out of 81) primary NSCLC specimens demonstrated hTERT amplification, which was significantly more common (P<0.001) in adenocarcinoma (30 out of 40) than in squamous cell carcinoma (13 out of 37). The hTERT mRNA overexpression was noted in 74% (94 out of 130) of tumours; it was more frequent in squamous cell than in adenocarcinoma (87 vs 68%, P=0.03). Overexpression was significantly associated with amplification (P=0.03), especially in adenocarcinoma. The hTERT gene amplification was prognostic for shorter recurrence-free survival (hazard ratio=2.16, P=0.03). These data indicate that gene amplification is an important mechanism for hTERT overexpression in lung adenocarcinoma and is an independent poor prognostic marker for disease-free survival in NSCLC.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| 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 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".