Genome-wide profiling at methylated promoters in pancreatic adenocarcinoma
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Bibliographic record
Abstract
UNLABELLED: Many genes undergo aberrant methylation in human cancers, and microarray platforms enable more comprehensive profiling of aberrant DNA methylation patterns. RESULTS: 1,010 of 87,922 probes on the 88 K promoter array (606 genes) had a higher signal (log(2) > 2) in the pancreatic cancer line, Panc-1 compared to the non-neoplastic pancreatic duct line, HPDE. Using this cut-off, bisulfite sequencing and/or MSP confirmed differential methylation of all 27 genes (66 probes) predicted to be methylated by the MCA array. More than 1/2 of the genes aberrantly hypermethylated in Panc-1 were not expressed in the pancreatic duct (HPDE) by expression array analysis. Using the 244 K CpG island array, 1,968 CpG islands were differentially methylated in MiaPaca2 compared to normal pancreas. The MCA method was more likely to identify hypermethylation within CpG islands than a cocktail of methylation sensitive restriction enzymes. DNA methylation profiles using 10 ng of DNA were highly correlated with those obtained using 5 ug of DNA (R2 = 0.98). Analysis of 57 pancreatic cancers and 34 normal pancreata using MSP identified MDFI, hsa-miR-9-1, ZNF415, CNTNAP2 and ELOVL4 as methylated in 96%, 89%, 86%, 82% and 68% of the cancers vs. 9%, 15%, 6%, 3% and 97% of normal pancreata, respectively. METHODS: We used methylated CpG island amplification (MCA) and Agilent promoter and CpG island microarrays to identify differential DNA methylation patterns in pancreatic cancer vs. normal pancreas. We examined MCA array reproducibility, compared it to methylation profiles obtained using a cocktail of methylation-sensitive restriction enzymes and examined gene expression of methylated genes. CONCLUSION: Promoter and CpG island array analysis finds aberrant methylation of hundreds of promoters and CpG islands in pancreatic cancer cells.
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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) | 0.000 | 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 it