Assessment of the InSiGHT Interpretation Criteria for the Clinical Classification of 24<i>MLH1</i>and<i>MSH2</i>Gene Variants
Bibliographic record
Abstract
Pathogenicity assessment of DNA variants in disease genes to explain their clinical consequences is an integral component of diagnostic molecular testing. The International Society for Gastrointestinal Hereditary Tumors (InSiGHT) has developed specific criteria for the interpretation of mismatch repair (MMR) gene variants. Here, we performed a systematic investigation of 24 MLH1 and MSH2 variants. The assessments were done by analyzing population frequency, segregation, tumor molecular characteristics, RNA effects, protein expression levels, and in vitro MMR activity. Classifications were confirmed for 15 variants and changed for three, and for the first time determined for six novel variants. Overall, based on our results, we propose the introduction of some refinements to the InSiGHT classification rules. The proposed changes have the advantage of homogenizing the InSIGHT interpretation criteria with those set out by the Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) consortium for the BRCA1/BRCA2 genes. We also observed that the addition of only few clinical data was sufficient to obtain a more stable classification for variants considered as "likely pathogenic" or "likely nonpathogenic." This shows the importance of obtaining as many as possible points of evidence for variant interpretation, especially from the clinical setting.
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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 | 0.001 | 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) | 0.000 | 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".