Germline mutations in seemingly sporadic pancreatic cancer.
Bibliographic record
Abstract
312 Background: Genetic predisposition underlies approximately 10% of pancreatic cancer (PC). Germline mutations in BRCA1, BRCA2, PALB2, ATM, TP53, MLH1, MSH2, MSH6, PMS2, PRSS1, APC, BMPR1A, STK11, CDKN2A, and SMAD4 are associated with PC susceptibility. Since young onset is not a hallmark of hereditary PC, we have hypothesized that seemingly sporadic cases may carry germline mutations in these genes. Methods: To investigate the prevalence of germline mutations in these 15 genes among sporadic PC cases, we analyzed lymphocyte DNA next generation sequencing data from 296 PC cases ascertained over 1 year from two PC referral centers in Toronto and Montreal. Results: We identified 21 mutations in 5 of the 15 genes (10 in BRCA2, 2 in BRCA1, 5 in ATM, 1 in p16, 3 in PRSS1) in 19 individuals. One individual carried two BRCA2 mutations that are usually observed together, and another individual carried both a PRSS1 and ATM mutation, however, in the absence of pancreatitis, PRSS1 mutations are not known to increase risk of PC. Incidences of 1.7% and 4.1% in ATM and BRCA-1 or -2 were observed. Approximately half of these mutations (4/9 for BRCA2, 1/2 for BRCA1, and 1/1 for p16) were known founder mutations in the French Canadian, Ashkenazi Jewish, Dutch or Asian populations. Since the role of ATMin PC predisposition remains under investigation, we obtained further evidence by testing for loss of the wild-type allele in cases with available tumor tissue. We observed loss of the wild-type allele in the 2 cases tested. Interestingly, the final pathology for the resected specimen from one of these two cases favored an ampullary cancer rather than a PC diagnosis. Conclusions: Since there are screening implications for the relatives of carriers and potentially treatment considerations for patients using therapies targeting DNA repair defects, these findings suggest a role for reflex testing of incident cases for at least population-specific recurrent mutations. Our findings also suggest that ATM germline mutations may give rise to ampullary cancer, underlie 1.4% of incident PC cases and imply broader testing considerations. For patients, testing may direct therapy choices if these tumors are targetable using agents that exploit DNA repair defects.
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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 | 0.000 | 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 | 0.000 | 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) | 0.003 | 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".