383. DEVELOPMENT OF PERSONALIZED ‘LIQUID BIOPSY’ FOR ESOPHAGEAL ADENOCARCINOMA FROM MATCHED ORGANOID CULTURE
Bibliographic record
Abstract
Abstract Background Recurrent mutations are not a hallmark of esophageal adenocarcinoma (EAC). This challenges the identification of circulating tumor DNA in the plasma and can limit the development of liquid biopsy strategies. We have cultured patient-derived EAC organoids and hypothesize that these can be used as a roadmap for the identification of circulating tumor DNA in the corresponding patient’s blood. Methods EAC tumor tissue from patients was processed to generate patient-derived organoids (PDOs) in Matrigel domes. Established PDOs were then scaled-up in suspension culture. To isolate mononucleosomes (147 bp), chromatin from these cells was extracted and digested with micrococcal nuclease (MNase). Right size selection was used to remove DNA larger than the targeted 147 bp. Next Generation Sequencing will be performed for nucleosome mapping and to generate a personlized SNV map. Using the SNV map, a personalized PCR panel will be developed to detect circulating tumor somatic variants in patient plasma cfDNA. Results DNA from three different PDOs were collected and MNase digested. MNase concentration and digestion time were optimized for each sample to avoid over digestion. MNase digestion resulted in mononucleosomes at approximately 147 bp for all three samples, as well as large DNA segments between 300 to 8000 bp. Right size selection resulted in isolation of 34 to 48 ng of the mononucleosome peak. These results indicate that MNase digestion was successful in generating nucleosomes of the desired size range and the selected nucleosomes were of high quality, as confirmed by the Bioanalyzer. Samples will be subjected to next-generation sequencing. Conclusion This study will determine nucleosome SNVs maps in circulating cell-free DNA from EAC patients to allow for generation of optimized targeted PCR panels, prediction of recurrence based on specific variants unique to each patient, and development of more precise drug screening. These advantages have the potential to fill a void in early cancer detection and the prediction of cancer recurrence, leading to improved prognoses for individuals diagnosed with 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 | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".