Towards personalized induction therapy for esophageal adenocarcinoma: organoids derived from endoscopic biopsy recapitulate the pre-treatment tumor
Bibliographic record
Abstract
Esophageal adenocarcinoma has few known recurrent mutations and therefore robust, reliable and reproducible patient-specific models are needed for personalized treatment. Patient-derived organoid culture is a strategy that may allow for the personalized study of esophageal adenocarcinoma and the development of personalized induction therapy. We therefore developed a protocol to establish EAC organoids from endoscopic biopsies of naïve esophageal adenocarcinomas. Histologic characterization and molecular characterization of organoids by whole exome sequencing demonstrated recapitulation of the tumors' histology and genomic (~ 60% SNV overlap) characteristics. Drug testing using clinically appropriate chemotherapeutics and targeted therapeutics showed an overlap between the patient's tumor response and the corresponding organoids' response. Furthermore, we identified Barrett's esophagus epithelium as a potential source of organoid culture contamination. In conclusion, organoids can be robustly cultured from endoscopic biopsies of esophageal adenocarcinoma and recapitulate the originating tumor. This model demonstrates promise as a tool to better personalize therapy for esophageal adenocarcinoma patients.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 teacher head, 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".