A Molecular Reappraisal of Glomus Tumors and Related Pericytic Neoplasms With Emphasis on NOTCH-gene Fusions
Bibliographic record
Abstract
Glomus tumors (GTs), together with myofibroma (MF), myopericytoma (MP), and angioleiomyoma (AL) are classified as members of the perivascular myoid family of tumors. The reported genetic abnormalities across these neoplasms is dissimilar, arguing against a pathogenetically unified family; half of the GT showing NOTCH-gene fusions and a smaller subset BRAF V600E mutations, while PDGFRB mutations are noted in a subset of MF and MP. This study aimed to investigate the prevalence and specificity of NOTCH-gene fusions in a large group of GT and correlate with clinical features. BRAF-VE1 and PDGFRB immunoexpression was also investigated in this cohort. A total of 93 GT and 43 other pericytic lesions (11 MP, 13 MF, and 19 AL) were selected. All cases were tested by fluorescence in situ hybridization for NOTCH1-4 and MIR143 gene abnormalities and 6 cases were investigated by targeted RNA-sequencing. Fluorescence in situ hybridization revealed NOTCH-gene rearrangements in 50 (54%) GT, 2 MP (18%), and 2 AL (11%). NOTCH-rearrangements were present in 34 (68%) benign and 16 (32%) malignant GT. Fusion-positive benign GT were overwhelmingly seen in males with a predilection for extremities, while the malignant GT occurred mostly in viscera. Among the fusion-negative GT, 88% were benign, 9% uncertain malignant potential, and 2% malignant. Half of the fusion-negative GTs occurred in the finger/subungual region. In summary, rearrangements of NOTCH genes are seen in over half of GT, with NOTCH2-MIR143 being the most common fusion (73%), while only a small subset of AL and MP share these abnormalities. The common subungual GT subset lack NOTCH-gene fusions suggesting an alternative pathogenesis. BRAF-VE1 was negative in all 37 cases studied, while strong PDGFRB staining was seen in 14 (21%) cases. Additional studies are needed to investigate the genetic alterations in the fusion-negative cases.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".