Msh2 deficiency increases the mutation frequency in all parts of the mouse colon
Bibliographic record
Abstract
The Msh2 DNA mismatch repair gene is one of five genes implicated in the pathogenesis of hereditary nonpolyposis colorectal cancer (HNPCC). To address the possible mechanisms of the site-specific occurrence of HNPCC, the effect of Msh2 deficiency on mutations in different parts of the colon was investigated using the BC-1(lacI)/Msh2 double transgenic mouse. Compared to the Msh2(+/+) mice, Msh2(-/-) mice had an 8-9-fold increase of mutation frequency (MF) in the lacI gene from the cecum and the proximal and distal colon. The mutational spectra were also significantly different between Msh2(+/+) and Msh2(-/-) mice, with a significant increase in the frequency of -1 frameshifts and G:C-->A:T base substitutions in the repair-deficient mice. However, in spite of the site-specific predisposition of HNPCC in humans, we found no significant difference in the MF or mutation spectrum between the three parts of the colon in Msh2(+/+), Msh2(+/-), or Msh2(-/-) mice. In addition, 11 independent mutants harboring complex mutations within the lacI gene were recovered in the Msh2(-/-) mice. Interestingly, while the Msh2(+/-) mice displayed an overall MF similar to that observed in the wild-type mice, sequencing revealed a significantly different mutational spectrum between Msh2(+/+) and Msh2(+/-) mice, mainly characterized by an increase in -1 frameshifts. Due to the prevalence of frameshift mutations in HNPCC patients, this haploinsufficiency effect of the Msh2 gene in safeguarding genomic integrity may have important implications for human carrier status.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".