Inducible nitric oxide synthase, nitrotyrosine and p53 mutations in the molecular pathogenesis of Barrett's esophagus and esophageal adenocarcinoma
Bibliographic record
Abstract
Nitric oxide (NO) has been implicated as a potential causative factor for endogenous p53 mutations in gastrointestinal malignancy. To investigate the role of NO in esophageal adenocarcinoma (EADC), we studied patterns of p53 mutations, expression of inducible nitric oxide synthase (iNOS) and the tissue accumulation of nitrotyrosine (NTS), a stable reaction product of NO and a marker for cellular protein damage, in human premalignant and malignant esophageal epithelia. Tissues were obtained from patients with gastroesophageal reflux disease (GERD)-induced esophagitis (n = 76), Barrett's esophagus (BE; n = 119) and primary EADC (n = 54). DNA sequencing was used to characterize p53 mutations, RT-PCR to study iNOS mRNA expression, and immunohistochemistry to study NTS. Relative to self-matched normal epithelia, a progressive increase in iNOS mRNA expression was seen in GERD (30%; 23/76), BE (48%; 57/119), and EADC (63%; 34/54) tissues (P < 0.001). Among patients with EADC, elevated levels of NTS immunoreactivity were more frequent in tumors with p53 mutations (11/21; 52%) compared with tumors with wild-type p53 (9/33; 27%; P = 0.063), and specifically in tumors with p53 mutations at CpG dinucleotides (10/12; 83%) compared with non-CpG p53 mutations (1/9; 11%; P = 0.008). The increasing frequency of iNOS (mRNA) overexpression in GERD, BE and EADC supports the hypothesis that an active inflammatory process, most likely a consequence of GERD, underlies molecular progression to EADC. The highly significant association between NTS, reflecting chronic NO-induced cellular protein damage, and endogenous p53 mutations at CpG dinucleotides, provides further evidence for a molecular link between chronic inflammation and esophageal malignancy.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".