Aberrant methylation of multiple genes in the upper aerodigestive tract epithelium of heavy smokers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
An important method for silencing tumor suppressor genes in cancers is by aberrant methylation (referred to as methylation) of CpG islands in gene promoter regions. In lung cancer, methylation of the genes retinoic acid receptor beta-2 (RARbeta-2), CDH13 (H-cadherin), p16(INK4a) (p16), RASSF1A (RAS association domain family I) is frequent. Thus, we investigated methylation of these genes in 4 different types of specimens (oropharyngeal brushes, sputum samples, bronchial brushes and bronchioloalveolar lavage [BAL] samples) of the upper aerodigestive tract epithelium from heavy smokers without evidence of cancer but with morphometric evidence of sputum atypia and compared the frequencies of methylation in the different types of specimens. In addition, we also analyzed sputum samples from 30 never smokers for methylation of these genes. Our major findings are: (i) At least one gene was methylated in one or more specimens from 48% of the smokers. However, methylation was statistically significant less frequently in never smokers compared to smokers. (ii) In general, methylation occurred more frequently in samples from the central airways (sputum, bronchial brushes) compared to the peripheral airways (BAL) and only occasionally in the oropharynx. (iii) RARbeta-2 was the most frequently methylated gene, whereas the frequency of methylation for the other genes was lower. (iv) Data from sputum samples and bronchial brushes were comparable. Our findings suggest that detection of methylation should be investigated as an intermediate marker for lung cancer risk assessment and response to chemopreventive regimens.
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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) | 0.000 | 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) | 0.000 | 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 it