A Multiplex SNaPshot Assay is a Rapid and Cost-Effective Method for Detecting POLE Exonuclease Domain Mutations in Endometrial Carcinoma
Bibliographic record
Abstract
Determining the replicative DNA polymerase epsilon ( POLE) mutation status in endometrial carcinomas (ECs) has important clinical implications given that the majority of "ultramutated" tumors harboring pathogenic exonuclease domain mutations in POLE ( POLE mut) have a favorable prognosis, even among high-grade histotypes. Currently, there are no specific morphologic or immunophenotypic features that allow accurate detection of POLE mut tumors without molecular testing. Consequently, identifying POLE mut tumors has been challenging without employing costly and/or time-consuming DNA sequencing approaches. Here we developed a novel SNaPshot assay to facilitate routine and efficient POLE mutation testing in EC. The SNaPshot assay interrogates 15 nucleotide sites within exons 9, 11, 13, and 14 encoding the POLE exonuclease domain. The variant sites were selected based on recurrence, evidence of functional impact, association with high tumor mutation burden and/or detection in EC clinical outcome studies. Based on the pathogenic somatic variants reported in the literature, the assay is predicted to have a clinical sensitivity of 90% to 95% for ECs. Validation studies showed 100% specificity and sensitivity for the variants covered, with expected genotypic results for both the positive (n=11) and negative (n=20) patient controls on multiple repeat tests and dilution series. Analytic sensitivity was conservatively approximated at a 10% variant allele fraction (VAF), with documented detection as low as 5% VAF. As expected, the SNaPshot assay demonstrated greater sensitivity than Sanger sequencing for VAFs below 20%, an important characteristic for somatic mutation detection. Here we have developed and validated the first SNaPshot assay to detect hotspot POLE mutations. While next-generation sequencing and Sanger sequencing-based approaches have also been used to detect POLE mutations, a SNaPshot approach provides useful balance of analytical sensitivity, cost-effectiveness, and efficiency in a high-volume case load setting.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".