Mismatch repair genes founder mutations and cancer susceptibility in Lynch syndrome
Bibliographic record
Abstract
Founder mutations in specific populations are common in several Mendelian disorders. They are shared by apparently unrelated families that inherited them from a common ancestor that existed hundreds to thousands of years ago. They have been proven to impact in molecular diagnostics strategies in specific populations, where they can be assessed as the first screening step and, if positive, avoid further expensive gene scanning. In Lynch syndrome (LS), a dominantly inherited colorectal cancer disease, more than 50 founder pathogenic mutations have been described so far in the mismatch repair (MMR) genes (MLH1, MSH2, MSH6 and PMS2). We here provide a comprehensive summary of the founder mutations found in the MMR genes and an overview of their main characteristics. At a time when high-throughput strategies are being introduced in the molecular diagnostics of cancer, genetic testing for founder mutations can complement next generation sequencing (NGS) technologies to most efficiently identify MMR gene mutations in any given population. Additionally, special attention is paid to MMR founder mutations with interesting anthropological significance.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".