The Utility of BRAFV600E Mutation-specific Antibody for Colon Cancers With Microsatellite Instability
Bibliographic record
Abstract
This study's objective was to assess the performance of immunohistochemical staining with the BRAF mutation-specific antibody (clone VE1) in tissue from colon cancers, including those with a high degree of microsatellite instability (MSI-H). VE1 was applied to tissue microarrays of 152 colon cancers with known MSI status. Results of immunohistochemical analyses were scored as negative, positive, or equivocal. The results of VE1 immunohistochemical analysis were compared with BRAF mutation analysis by PCR. Fifteen of the 152 cases (10%) were positive with VE1 immunohistochemical analysis, 8 were equivocal, and 129 were negative. There was a single false-negative case and no false positives were identified when 74 VE1-positive or VE1-negative cases were tested by the BRAF PCR testing. Of the 8 equivocal VE1 cases identified, 3 were BRAF-positive. In the 17 MSI-H colon cancers, VE1 immunohistochemical analysis resulted in 7 true-positive, 9 true-negative, and 1 false-negative case when compared with PCR results. The sensitivity and specificity of VE1 in the MSI-H colon cancer group were determined to be 88% and 100%, respectively. The BRAF positivity rate by VE1 immunohistochemical analysis in MSI-H colon cancers is consistent with that of published cohorts, which use molecular assays, and the accuracy of positive or negative VE1 staining is high. A small subset of equivocal cases (5% in our cohort) with heterogenous staining requires confirmation by the BRAF mutation analysis. We propose a testing algorithm for Lynch syndrome screening in MSI-H colorectal cancers that incorporates VE1 immunohistochemical analysis with PCR testing for equivocal cases.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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".