A novel group of spindle cell tumors defined by S100 and CD34 co‐expression shows recurrent fusions involving RAF1, BRAF, and NTRK1/2 genes
Bibliographic record
Abstract
Tumors characterized by co-expression of S100 and CD34, in the absence of SOX10, remain difficult to classify. Triggered by a few index cases with monomorphic cytomorphology and distinctive stromal and perivascular hyalinization, immunopositivity for S100 and CD34, and RAF1 and NTRK1 fusions, the authors undertook a systematic review of tumors with similar features. Most of the cases selected were previously diagnosed as low-grade malignant peripheral nerve sheath tumors, while others were deemed unclassified. The tumors were studied with targeted RNA sequencing and/or FISH. A total of 25 cases (15 adults and 10 children) with kinase fusions were identified, including 8 cases involving RAF1, 2 BRAF, 14 NTRK1, and 1 NTRK2 gene rearrangements. Most tumors showed a monomorphic spindle cell proliferation with stromal and perivascular keloidal collagen, in a patternless architecture, with only occasional scattered pleomorphic or multinucleated cells. Most cases showed low cellularity, a low mitotic count, and absence of necrosis. Although a subset showed overlap with lipofibromatosis-like neural tumors, the study group showed distinctive hyalinization and overt malignant features, such as highly cellular fascicular growth and primitive appearance. All tumors showed co-expression of S100 and CD34, ranging from focal to diffuse. SOX10 was negative in all cases. NTRK1 immunohistochemistry showed high levels of expression in all tumors with NTRK1 gene rearrangements. H3K27me3 expression performed in a subset of cases was retained. These findings together with the recurrent gene fusions in RAF1, BRAF, and NTRK1/2 kinases suggest a distinct molecular tumor subtype with consistent S100 and CD34 immunoreactivity.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| 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) | 0.001 | 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".