The associated contributions of p53 and the DNA mismatch repair protein Msh6 to spontaneous tumorigenesis
Bibliographic record
Abstract
DNA mismatch repair (MMR) is a highly conserved system that repairs DNA adducts acquired during replication, as well as some forms of exogenous/endogenous DNA damage. Additionally, MMR proteins bind to DNA adducts that are not removed by MMR and influence damage-response mechanisms other than repair. Hereditary non-polyposis colorectal cancer, as well as mouse models for MMR deficiency, illustrate that MMR proteins are required for maintenance of genetic stability and tumor suppression. In both humans and mice, the phenotype associated with Msh6-associated tumorigenesis is distinct from that of Msh2. In this study, we hypothesized that Msh6-/-;p53+/- mice would display earlier tumor onset than their Msh6-/- or p53+/- counterparts, indicating that concomitant loss of these two tumor suppressors contributes to tumorigenesis via mechanisms that are only partially interrelated. We generated a Msh6-/-;p53+/- mouse model which succumbed to malignant disease at an accelerated rate and with a tumor spectrum distinct from both Msh6-/- and p53+/- models. Alteration of tumor phenotype in the Msh6-/-;p53+/- mice included a marked increase in microsatellite instability that was associated with loss of heterozygosity of the remaining p53 allele. Also, genetic instability was inversely correlated with survival. This manuscript marks the first in vivo investigation into the association between Msh6 and p53, and their combined role in the suppression of spontaneous tumorigenesis, cell survival and genomic stability. Our results support the hypothesis that p53 and Msh6 are functionally interrelated and that, with concomitant mutation, these tumor suppressors act together to accelerate tumorigenesis.
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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 | 0.000 | 0.001 |
| 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 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".