Telomerase reverse transcriptase immunohistochemical expression is sensitive but not specific for <i>TERT</i> gene amplification in acral melanoma
Bibliographic record
Abstract
BACKGROUND: TERT gene amplification (TGA) is a mechanism of telomerase reverse transcriptase (TERT) upregulation frequently utilized by acral melanomas (AMs). Currently, the utility of TERT immunohistochemistry (IHC) to predict TGA status in AMs is poorly documented. METHODS: AMs (26 primary and 3 metastatic) and non-acral cutaneous melanomas (6 primary) were subjected to immunohistochemical analysis using anti-TERT antibody to demonstrate protein expression and fluorescence in situ hybridization (FISH) to assess genomic copy number alteration. The relationship between TERT immunoreactivity and TGA confirmed by FISH was assessed using logistic regression. RESULTS: TERT expression was seen in 50% (13/26) of primary and 100% (3/3) of metastatic AMs and 50% (3/6) of primary non-acral cutaneous melanomas. TGA was found in 15% (4/26) and 67% (2/3) of primary and metastatic AMs and 17% (1/6) of non-acral cutaneous melanomas. The intensity of TERT immunoreactivity correlated with TGA (p = 0.04) and a higher TERT copy number-to-control ratio in AMs, with a correlation coefficient of 0.41 (p = 0.03). The sensitivity and specificity of TERT immunoreactivity for predicting TGA in AMs were 100% and 57%, with corresponding positive and negative predictive values of 38% and 100%, respectively. CONCLUSIONS: The clinical utility of TERT IHC to predict TGA status in AMs appears to be limited given its low specificity and positive predictive value.
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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 | 0.001 | 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 | 0.001 |
| 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".