Genetic and Epigenetic Alterations of Familial Pancreatic Cancers
Bibliographic record
Abstract
BACKGROUND: Little is known about the genetic and epigenetic changes that contribute to familial pancreatic cancers. The aim of this study was to compare the prevalence of common genetic and epigenetic alterations in sporadic and familial pancreatic ductal adenocarcinomas. METHODS: DNA was isolated from the microdissected cancers of 39 patients with familial and 36 patients with sporadic pancreatic adenocarcinoma. KRAS2 mutations were detected by BstN1 digestion and/or cycle sequencing. TP53 and SMAD4 status were determined by immunohistochemistry on tissue microarrays of 23 archival familial pancreatic adenocarcinomas and in selected cases by cycle sequencing to identify TP53 gene mutations. Methylation-specific PCR analysis of seven genes (FoxE1, NPTX2, CLDN5, P16, TFPI-2, SPARC, ppENK) was done on a subset of fresh-frozen familial pancreatic adenocarcinomas. RESULTS: KRAS2 mutations were identified in 31 of 39 (80%) of the familial versus 28 of 36 (78%) of the sporadic pancreatic cancers. Positive immunolabeling for p53 was observed in 57% of the familial pancreatic cancers and loss of SMAD4 labeling was observed in 61% of the familial pancreatic cancers, rates similar to those observed in sporadic pancreatic cancers. The mean prevalence of aberrant methylation in the familial pancreatic cancers was 68.4%, which was not significantly different from that observed in sporadic pancreatic cancers. CONCLUSION: The prevalence of mutant KRAS2, inactivation of TP53 and SMAD4, and aberrant DNA methylation of a seven-gene panel is similar in familial pancreatic adenocarcinomas as in sporadic pancreatic adenocarcinomas. These findings support the use of markers of sporadic pancreatic adenocarcinomas to detect familial pancreatic adenocarcinomas.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".