347. LASER CAPTURE MICRODISSECTION AND WHOLE GENOME SEQUENCING OF ESOPHAGEAL ADENOCARCINOMA SAMPLES WITH MINIMAL TUMOUR
Bibliographic record
Abstract
Abstract Background Esophageal adenocarcinoma (EAC) samples, particularly biopsies, can have low tumour cellularity, which limits their use for sequencing. Previous studies have focused on untreated resection specimens with high cellularity (i.e. TCGA requiring 60% cellularity on histology). Laser capture microdissection (LCM) is a method to enrich tumour cells from histological specimens and has been successfully used in other samples. We hypothesize that LCM can enrich for tumour from biopsies and resection specimens with very low cellularity. Methods Biopsy and resection EAC specimens were subjected to laser capture microdissection and whole genome sequencing (N = 49 biopsies and N = 15 resections) as part of the MOCHA trial (NCT04219137). LCM samples were reviewed by a board-certified pathologist to quantify tumour cellularity prior to LCM. Matched germline DNA was extracted from patient blood. Samples were processed using an in-house pipeline to call somatic single nucleotide variants (SNVs), insertions, deletions, copy number changes, and structural variants. Post LCM tumour cellularity was estimated from the WGS data. Results We had slightly higher WGS tumour cellularity for biopsies (66.2% +/− 16.8) and resections (71.3% +/− 18.0) than TCGA (58.1% +/− 17.5), while our histological cellularity was much lower than TCGA’s 60% cutoff at 32.2% +/− 24.5 for biopsies and 31.0% +/− 22.7 for resections. Overall, our LCM strategy led to an increase of 35.4 +/− 25.1% for cellularity by WGS compared to the histology. Finally, we observed a similar tumour ploidy and SNV composition as TCGA, which further verified that our tumour enrichment strategy was successful. Conclusion We have successfully applied an LCM strategy to enrich for tumour cells from low cellularity specimens. For example, we have successfully enriched for tumour cells from specimens with as low as 1% histological cellularity. We are currently exploring the results of this dataset including clinical correlations, changes in potential driver mutations from biopsy to resection, and comparing our results to treatment response.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".