Evidence that dysregulated DNA mismatch repair characterizes human nonmelanoma skin cancer
Bibliographic record
Abstract
BACKGROUND: In addition to an established role in the repair of postreplicative DNA errors, DNA mismatch repair (MMR) proteins also contribute to cellular responses to exogenous DNA damage. Previously, we have shown that Msh2-null mice display increased sensitivity to ultraviolet (UV) B-induced tumorigenesis, but squamous cell carcinomas (SCC) generated are microsatellite stable, suggesting a role for MMR other than postreplicative repair in UV-induced cutaneous tumour formation. OBJECTIVES: We questioned whether there was evidence of MMR dysfunction in human SCC, thus validating the mouse models of MMR-dependent UVB-induced skin cancer. METHODS: Using tissue microarrays we examined both nuclear and cytoplasmic levels of MMR proteins MSH2, MSH6, MSH3, MLH1 and PMS2 in more than 200 cases of cutaneous SCC and basal cell carcinoma (BCC). RESULTS: We found that subsets of these 10 MMR protein measures were increased in nonmelanoma skin cancer (NMSC) compared with normal epidermal samples; this was particularly true of SCC. In fact, based on post hoc tests and MMR protein distribution patterns, BCC was distinct from SCC. With the exception of nuclear MSH2, the BCC had lower levels of identified MMR protein measures than SCC. We believe this to be important because not only is SCC more aggressive than BCC, but evidence suggests that these two NMSC subtypes arise through different molecular pathways. CONCLUSIONS: In combination with previously established roles for MMR proteins in response to UVB-induced DNA damage, our data point towards an expanded perspective of the importance of MMR proteins in the suppression of UVB-induced tumorigenesis and, potentially, tumour behaviour.
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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 | 0.000 | 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 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".