High Content Imaging of Barrett’s-Associated High-Grade Dysplasia Cells After siRNA Library Screening Reveals Acid-Responsive Regulators of Cellular Transitions
Bibliographic record
Abstract
BACKGROUND & AIMS: Esophageal adenocarcinoma (EAC) develops from within Barrett's esophagus (BE) concomitant with gastroesophageal reflux disease (GERD). Wound healing processes and cellular transitions, such as epithelial-mesenchymal transitions, may contribute to the development of BE and the eventual migratory escape of metastatic cancer cells. Herein, we attempt to identify the genes underlying esophageal cellular transitions and their potential regulation by the low pH environments observed in GERD and commonly encountered by escaping cancer cells. METHODS: Small interfering RNA library screening and high-content imaging analysis outlined changes in BE high-grade dysplasia (HGD) and EAC cell morphologies after gene silencing. Gene expression microarray data and low pH exposures studies modeling GERD-associated pulses (pH 4.0, 10 min) and tumor microenvironments (pH 6.0, constant) were used. RESULTS: Statistical analysis of small interfering RNA screening data defined 207 genes (Z-score >2.0), in 12 distinct morphologic clusters, whose suppression significantly altered BE-HGD cell morphology. The most significant genes in this list included KIF11, RRM2, NUBP2, P66BETA, DUX1, UBE3A, ITGB8, GAS1, GPS1, and PRC1. Guided by gene expression microarray study data, both pulsatile and constant low pH exposures were observed to suppress the expression of GPS1 and RRM2 in a nonoverlapping temporal manner in both BE-HGD and EAC cells, with no changes observed in squamous esophageal cells. Functional studies uncovered that GPS1 and RRM2 contributed to amoeboid and mesenchymal cellular transitions, respectively, as characterized by differential rates of cell motility, pseudopodia formation, and altered expression of the mesenchymal markers vimentin and E-cadherin. CONCLUSIONS: Collectively, we have shown that low pH microenvironments associated with GERD, and tumor invasive edges, can modulate the expression of genes that triggered esophageal cellular transitions potentially critical to colonization and invasion.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".