Germline <i>BRCA2</i> K3326X and <i>CHEK2</i> I157T mutations increase risk for sporadic pancreatic ductal adenocarcinoma
Bibliographic record
Abstract
Rare truncating BRCA2 K3326X (rs11571833) and pathogenic CHEK2 I157T (rs17879961) variants have previously been implicated in familial pancreatic ductal adenocarcinoma (PDAC), but not in sporadic cases. The effect of both mutations in important DNA repair genes on sporadic PDAC risk may shed light on the genetic architecture of this disease. Both mutations were genotyped in germline DNA from 2,935 sporadic PDAC cases and 5,626 control subjects within the PANcreatic Disease ReseArch (PANDoRA) consortium. Risk estimates were evaluated using multivariate unconditional logistic regression with adjustment for possible confounders such as sex, age and country of origin. Statistical analyses were two‐sided with p values <0.05 considered significant. K3326X and I157T were associated with increased risk of developing sporadic PDAC (odds ratio (ORdom) = 1.78, 95% confidence interval (CI) = 1.26–2.52, p = 1.19 × 10−3 and ORdom = 1.74, 95% CI = 1.15–2.63, p = 8.57 × 10−3, respectively). Neither mutation was significantly associated with risk of developing early‐onset PDAC. This retrospective study demonstrates novel risk estimates of K3326X and I157T in sporadic PDAC which suggest that upon validation and in combination with other established genetic and non‐genetic risk factors, these mutations may be used to improve pancreatic cancer risk assessment in European populations. Identification of carriers of these risk alleles as high‐risk groups may also facilitate screening or prevention strategies for such individuals, regardless of family history.
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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 | 0.003 |
| 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 | 0.001 | 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".