Polymorphisms and HNPCC: PMS2-MLH1 protein interactions diminished by single nucleotide polymorphisms
Bibliographic record
Abstract
Hereditary nonpolyposis colorectal cancer (HNPCC) is one of the most common autosomal dominant inherited diseases. Mutations in the human mismatch repair (MMR) proteins MLH1, MSH2, MSH6, PMS1, and PMS2 have been found to co-segregate with HNPCC. The MLH1 and MSH2 proteins have been demonstrated to interact with PMS1, PMS2, and MSH6 proteins. A previous study reported that missense mutations in specific regions of MLH1 can lead to defects in protein-protein interactions with PMS2. Here we report that three missense alterations previously identified as single nucleotide polymorphisms (SNPs) in PMS2 (P511K, T597S, and M622I) cause defective protein-protein interactions with MLH1, even though the alterations are not in the previously reported interaction domain. These results suggest that an additional domain in PMS2 affects MLH1-PMS2 interaction. This study also demonstrates that SNPs can result in gene alterations that indeed have a functional effect on protein phenotype. Thus, these three SNPs may ultimately represent variants with an increased risk factor for tumorgenesis in HNPCC. This study is one of the first to use a functional assay to appraise the role of SNPs and suggests that traditional definitions of polymorphisms and mutations are in need of reconsideration.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".