Short telomeres in an oral precancerous lesion: Q‐FISH analysis of leukoplakia
Bibliographic record
Abstract
OBJECTIVES: A precancerous condition is a lesion that, if left untreated, leads to cancer or can be induced to become malignant. In the oral region, leukoplakia is a lesion that has been regarded as precancerous. In cases of oral carcinoma, we have frequently noticed that a type of leukoplakia histologically demonstrating hyper-orthokeratosis and mild atypia (ortho-keratotic dysplasia; OKD) is often associated with carcinoma, either synchronously or metachronously. Therefore, we consider OKD-type leukoplakia to be a true precancerous lesion. MATERIALS AND METHODS: In an attempt to clarify the relationship between OKD as a precancerous condition in the oral mucosa and telomere length, we estimated telomere lengths in this type of leukoplakia using quantitative fluorescence in situ hybridization, and also quantified the frequency of anaphase-telophase bridges (ATBs) in comparison with squamous cell carcinoma in situ (CIS) and the background tissues of CIS and OKD. RESULTS: Ortho-keratotic dysplasia was frequently associated with squamous cell carcinoma (45.0%) and showed significantly shorter telomeres than normal control epithelium, CIS, or the background of CIS or OKD. The frequency of ATBs was much higher in OKD than in control epithelium or CIS. CONCLUSION: Ortho-keratotic dysplasia appears to be frequently associated with carcinoma, chromosomal instability, and excessively shortened telomeres, not only in the lesion itself but also in the surrounding background. Therefore, when this type of leukoplakia is recognized in the oral region, strict follow-up for oral squamous cell carcinoma is necessary, focusing not only on the areas of leukoplakia, but also the surrounding background.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".