Loss of SMAD4 Is Sufficient to Promote Tumorigenesis in a Model of Dysplastic Barrett’s Esophagus
Bibliographic record
Abstract
BACKGROUND & AIMS: Esophageal adenocarcinoma (EAC) develops from its precursor Barrett's esophagus through intermediate stages of low- and high-grade dysplasia. However, knowledge of genetic drivers and molecular mechanisms implicated in disease progression is limited. Herein, we investigated the effect of Mothers against decapentaplegic homolog 4 (SMAD4) loss on transforming growth factor β (TGF-β) signaling functionality and in vivo tumorigenicity in high-grade dysplastic Barrett's cells. METHODS: polymerase chain reaction arrays were used to analyze TGF-β signaling functionality, and low-coverage whole-genome sequencing was performed to detect copy number alterations upon SMAD4 loss. RESULTS: We found that SMAD4 knockout significantly alters the TGF-β pathway target gene expression profile. SMAD4 knockout positively regulates potential oncogenes such as CRYAB, ACTA2, and CDC6, whereas the CDKN2A/B tumor-suppressor locus was regulated negatively. We verified that SMAD4 in combination with CDC6-CDKN2A/B or CRYAB genetic alterations in patient tumors have significant predictive value for poor prognosis. Importantly, we investigated the effect of SMAD4 inactivation in Barrett's tumorigenesis. We found that genetic knockdown or knockout of SMAD4 was sufficient to promote tumorigenesis in dysplastic Barrett's esophagus cells in vivo. Progression to invasive EAC was accompanied by distinctive and consistent copy number alterations in SMAD4 knockdown or knockout xenografts. CONCLUSIONS: Altogether, up-regulation of oncogenes, down-regulation of tumor-suppressor genes, and chromosomal instability within the tumors after SMAD4 loss implicates SMAD4 as a protector of genome integrity in EAC development and progression. Foremost, SMAD4 loss promotes tumorigenesis from dysplastic Barrett's toward EAC.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".