The Immune Underpinnings of Barrett’s-Associated Adenocarcinogenesis: a Retrial of Nefarious Immunologic Co-Conspirators
Bibliographic record
Abstract
There is no doubt that chronic gastroesophageal reflux disease increases the risk of esophageal adenocarcinoma (EAC) by several fold (odds ratio, 6.4; 95% CI, 4.6-9.1), and some relationships between reflux disease-mediated inflammation and oncogenic processes have been explored; however, the precise interconnections between the immune response and genomic instabilities underlying these pathologic processes only now are emerging. Furthermore, the precise cell of origin of the precancerous stages associated with EAC development, Barrett's esophagus, be it cardia resident or embryonic remnant, may shape our interpretation of the likely immune drivers. This review integrates the current collective knowledge of the immunology underlying EAC development and outlines a framework connecting proinflammatory pathways, such as those mediated by interleukin 1β, tumor necrosis factor α, leukemia inhibitory factor, interleukin 6, signal transduction and activator of transcription 3, nuclear factor-κB, cyclooxygenase-2, and transforming growth factor β, with oncogenic pathways in the gastroesophageal reflux disease-Barrett's esophagus-EAC cancer sequence. Further defining these immune and molecular railroads may show a map of the routes taken by gastroesophageal cells on their journey toward EAC tumor phylogeny. The selective pressures applied by this immune-induced journey likely impact the phenotype and genotype of the resulting oncogenic destination and further exploration of lesser-defined immune drivers may be useful in future individualized therapies or enhanced selective application of recent immune-driven therapeutics.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.006 |
| 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".