Telomerase Activity Is Upregulated in Laryngeal Squamous Cell Carcinoma
Bibliographic record
Abstract
OBJECTIVE/HYPOTHESIS: The immortalizing enzyme telomerase has been linked to carcinogenesis and is being targeted as a novel molecular marker. This study investigated telomerase expression in patients with laryngeal squamous cell carcinoma and correlated telomerase activity with conventional prognostic parameters. STUDY DESIGN: A consecutive series of patients with laryngeal squamous cell carcinoma undergoing surgical salvage for persistent or progressive disease after failed radiation therapy. METHODS: Twenty patient samples of laryngeal squamous cell carcinoma and 20 adjacent histologically normal mucosal samples were assayed using the telomeric repeat amplification protocol (TRAP) method for detection of telomerase activity. The leukemic cell line, K562, acted as a positive control and the human fibroblast line, Hs21Fs, as a negative control. A sample was classified as telomerase positive when an RNase-sensitive hexameric repeat ladder was observed. Absence of laddering was considered a negative result. RESULTS: Seventeen of 20 (85%) tumor samples and 4 of 20 (20%) adjacent histologically normal samples were telomerase positive. No statistically significant difference was observed when densitometric readings were compared by T category, tumor grade, or site (by ANOVA). CONCLUSIONS: Although telomerase activity is present in laryngeal cancer, levels of activation do not correlate with conventional parameters used for prognostication. Our study indicates that the marker may be a useful adjunctive method in the diagnosis of malignancy after radiation failure.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".