Overview of major molecular alterations during progression from Barrett's esophagus to esophageal adenocarcinoma
Bibliographic record
Abstract
Esophageal adenocarcinoma (EAC) develops in the sequential transformation of normal epithelium into metaplastic epithelium, called Barrett's esophagus (BE), then to dysplasia, and finally cancer. BE is a common condition in which normal stratified squamous epithelium of the esophagus is replaced with an intestine-like columnar epithelium, and it is the most prominent risk factor for EAC. This review aims to impartially systemize the knowledge from a large number of publications that describe the molecular and biochemical alterations occurring over this progression sequence. In order to provide an unbiased extraction of the knowledge from the literature, a text-mining methodology was used to select genes that are involved in the BE progression, with the top candidate genes found to be TP53, CDKN2A, CTNNB1, CDH1, GPX3, and NOX5. In addition, sample frequencies across analyzed patient cohorts at each stage of disease progression are summarized. All six genes are altered in the majority of EAC patients, and accumulation of alterations correlates well with the sequential progression of BE to cancer, indicating that the text-mining method is a valid approach for gene prioritization. This review discusses how, besides being cancer drivers, these genes are functionally interconnected and might collectively be considered a central hub of BE progression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".