Chromosomal Instability in Barrett's Esophagus Is Related to Telomere Shortening
Bibliographic record
Abstract
Barrett's esophagus is a useful model for the study of carcinogenesis, as the metaplastic columnar epithelium that replaces squamous esophageal epithelium is at elevated risk for development of adenocarcinoma. We examined telomere length and chromosomal instability (CIN) in Barrett's esophagus biopsies using fluorescence in situ hybridization. To study CIN, we selected centromere and locus-specific arm probes to chromosomes 17/17p (p53), 11/11q (cyclin D1), and 9/9p (p16 INK4A), loci reported to be involved in early stages of Barrett's esophagus neoplasia. Telomere shortening was observed in Barrett's esophagus epithelium at all histologic grades, whereas CIN was highest in biopsies with dysplastic changes; there was, however, considerable heterogeneity between patients in each variable. Alterations on chromosome 17 were strongly correlated with telomere length (r = 0.55; P < 0.0001) and loss of the 17p arm signal was the most common event. CIN on chromosome 11 was also associated with telomere shortening (r =0.3; P = 0.05), although 11q arm gains were most common. On chromosome 9p, arm losses were the most common finding, but chromosome 9 CIN was not strongly correlated with telomere length. We conclude that CIN is related to telomere shortening in Barrett's esophagus but varies by chromosome. Whether instability is manifested as loss or gain seems to be influenced by the chromosomal loci involved. Because telomere shortening and CIN are early events in Barrett's esophagus neoplastic progression and are highly variable among patients, it will be important to determine whether they identify a subset of patients that is at risk for more rapid neoplastic evolution.
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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 | 0.001 | 0.001 |
| 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".