352. GENERATION OF PATIENT-DERIVED ESOPHAGEAL ADENOCARCINOMA ORGANOIDS FROM CIRCULATING TUMOR CELLS
Bibliographic record
Abstract
Abstract Background Esophageal adenocarcinoma (EAC) is diagnosed in nearly 40% of patients when their cancer has already metastasized. Circulating tumor cells (CTCs) play a critical role in the metastatic cascade and need to be investigated in the context of EAC, but these must be expanded due to their scarcity in blood. Organoid models have been shown to recapitulate tumor heterogeneity and in vivo drug sensitivity. Thus, we aim to generate and characterize CTC-derived organoids from EAC patients. Methods CTCs were isolated from 32 blood samples obtained from 13 EAC patients using two methods: (1) Ficoll-based density gradient centrifugation followed by CD45+ cell depletion using magnetic-activated cell sorting (MACS) and/or (2) immunodensity separation using the RosetteSep CTC Enrichment Cocktail (Stemcell Technologies). Isolated CTCs were embedded and grown in Matrigel domes. Cultures were dissociated into single cells which were magnetically labelled and captured on a microfluidic chip. The captured cells were stained with DAPI, anti-CD45, anti-CK11, anti-CK13, and anti-CK18 antibodies. These cells were then visualized and quantified using fluorescence microscopy. Results Organoids were generated from twenty-one out of thirty-two samples, after two to six weeks in culture, with an average of 20.76 ± 6.435 organoids per sample. These EAC CTC derived organoids underwent a growth arrest once they reached an arbitrary size but were able to regenerate upon dissociation and re-seeding. However, no increase in the size or number of organoids was observed post-passaging. Of the nine CTC-derived organoid samples characterized using microfluidic capture and immunostaining, all nine had the presence of CD45 negative, CK positive, and DAPI positive cells. Conclusion In this study, we validated commonly used CTC isolation methods and were able to demonstrate that CTCs isolated can be cultured to generate organoids. Additional investigation is required to overcome the growth arrest which occurs during culture.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".