A population‐based study of hereditary non‐polyposis colorectal cancer: evidence of pathologic and genetic heterogeneity
Bibliographic record
Abstract
Hereditary non-polyposis colorectal cancer (HNPCC) may be the result of Lynch syndrome (LS) caused by mutations in mismatch repair (MMR) genes, a syndrome of unknown etiology called familial colorectal cancer type-X (FCCTX), or familial serrated neoplasia associated with the colorectal cancer (CRC) somatic BRAF mutation. To determine the cause of HNPCC in the founder population of the island of Newfoundland, we studied 37 families with LS and 29 families without LS who fulfilled the Amsterdam I criteria. In non-LS, four index CRCs were BRAF mutation positive, one of which was microsatellite instable. Geographic clustering of LS families caused by three different founder mutations in MSH2 was observed. Nine unique MMR mutations in four MMR genes were identified in single families distributed in different geographic isolates. The geographic distribution of non-LS was similar to LS. The coefficient of relatedness using genotype data was significantly higher for non-LS than for all CRC. Extensive genealogic investigation failed to connect non-LS families and in some clusters pathologic CRC heterogeneity was observed. We conclude that non-LS HNPCC may be a heterogeneous disorder with different pathogenic pathways, and that the geographic distribution is consistent with multiple different mutations in unknown CRC susceptibility gene(s).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".