Oesophageal squamous cell carcinoma may develop within a background of accumulating DNA methylation in normal and dysplastic mucosa
Bibliographic record
Abstract
BACKGROUND: Oesophageal squamous cell carcinoma (OSCC) often arises from preceding dysplastic lesions in the oesophageal epithelium. However, the molecular changes occurring in premalignant lesions are not well understood. An epigenetic change is an example of OSCC that may occur within the epithelium. AIM: To investigate the methylation status of multiple promoters in cancer-derived DNA, as well as in the background epithelium of OSCC, including dysplastic lesions and non-neoplastic mucosa. The normal epithelium from patients without cancer was also examined. The findings were correlated with the mutational status of p53. PATIENTS AND METHODS: 56 patients with advanced OSCC, 21 patients with intraepithelial neoplasia (IEN), 56 patients with a background of non-neoplastic epithelium, adjacent to the OSCC, and 42 normal control epithelia from healthy volunteers were studied. The promoter methylation status of SFRP1, SFRP2, DCC, APC, p16(INK4a), p14(ARF), MINT1, MINT2, MINT31, CACNA1G, COX2, DAPK, hMLH1 and MGMT was examined by methylation-specific single polymerase chain reaction or combined bisulphite restriction analysis. The mutation of p53 by direct sequencing was assessed. RESULTS: DNA methylation was observed in OSCC and in its background epithelium. The frequency of CpG island methylation increased from a baseline level in the background non-neoplastic epithelium, through IEN, to advanced OSCC. However, mutations in p53 were almost exclusively observed in IEN and OSCC. More extensive DNA methylation was seen in the neoplastic lesions (OSCC or IEN) having a p53 mutation than in those with wild-type p53. CONCLUSION: DNA methylation is present at low levels in the non-neoplastic oesophageal epithelium and appears to contribute to the progression of the dysplasia-carcinoma sequence in OSCC carcinogenesis.
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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 | 0.001 |
| 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".