Plasma cell-free DNA methylome as early detection and prognostic marker for pancreatic cancer
Bibliographic record
Abstract
Abstract Pancreatic cancer is highly fatal, with limited early detection options. Here, we conducted a study to evaluate the potential use of circulating cell-free DNA methylation for pancreatic cancer early detection and prognosis. Using a highly sensitive enrichment-based sequencing technology, we profiled genome-wide circulating cell-free methylome of 199 pancreatic cancer patients and 205 healthy individuals. We identified a panel of differentially methylated regions in cell-free DNA that distinguished pancreatic cancer cases from controls with high accuracy (test set AUC=0.93, 95%CI=0.88-0.98), notably robust accuracy for early-stage pancreatic cancer (AUC=0.92, 95%CI=0.86-0.98). We also identified a panel of cfDNA methylated regions that effectively stratified patients into longer or shorter survival groups, which was independently validated in The Cancer Genome Atlas cohort (HR=1.37, 95%CI=1.00-1.88, p=0.049). These results provide support for the potential utility of cell-free DNA methylation markers for both early detection and prognosis in pancreatic cancer, presenting a promising tool for enhancing patient management.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".