Linkage analysis of chromosome 4 in families with familial pancreatic cancer
Bibliographic record
Abstract
BACKGROUND: Approximately 10% of pancreatic ductal adenocarcinomas have a familial basis. While a small portion of this familial clustering can be explained by inherited mutations in known genes (BRCA2, p16/CDKN2A, PRSS1, and STK11), the genetic basis for the majority of this familial clustering remains unknown. In addition, a pancreatic cancer susceptibility locus has been reported to be linked to chromosome 4q32-34 in a single family having a high penetrance of early-onset pancreatic ductal adenocarcinoma and pancreatic insufficiency. The goal of this study is to determine if linkage to chromosome 4q exists in our series of well-characterized families with idiopathic familial pancreatic cancer enrolled in the Pancreatic Cancer Genetic Epidemiology Consortium (PACGENE). METHODS: Parametric and nonparametric linkage analyses were performed using 21 microsatellite markers on chromosome 4 on affected individuals with pancreatic cancer from 42 familial pancreatic cancer kindreds. RESULTS: Markov Chain Monte Carlo parametric and nonparametric linkage analyses using SIMWALK2 as well as nonparametric linkage analysis using MERLIN did not provide strong evidence of linkage in this region (LOD < 1.0). Only one family provided a multipoint LOD score of >0.5 adjacent to the reported region. CONCLUSIONS: Our results do not support linkage to the 4q32-34 region in the majority of our familial pancreatic cancer kindreds. However, because multiple pancreatic cancer susceptibility genes are likely to exist, it is possible that a subset of the families in this study may be linked to this region.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".