Spindle Cell Tumors With RET Gene Fusions Exhibit a Morphologic Spectrum Akin to Tumors With NTRK Gene Fusions
Bibliographic record
Abstract
A major breakthrough in the classification of soft tissue tumors has been the recent identification of NTRK-fusion related neoplasms which are amenable to highly effective targeted therapies. Despite these therapeutic opportunities, diagnostic challenges have emerged in recognizing tumors characterized by protein kinase fusions, as they are associated with a wide morphologic spectrum, variable risk of malignancy and a rather nonspecific immunoprofile. As such, NTRK-related fusions may occur in infantile fibrosarcoma, lipofibromatosis-like neural tumors (LPF-NTs), tumors resembling malignant peripheral nerve sheath tumors, etc. Triggered by an index case resembling LPF-NT but harboring RET gene rearrangement, we investigated our files for cases showing RET gene abnormalities to establish their clinicopathologic features. Tumors were tested with a combination of targeted RNA sequencing and fluorescence in situ hybridization methods. Six cases with RET gene rearrangements were identified, all except 1 occurred in children, including 4 infants. Their morphologic spectrum was quite diverse, but closely reproduced the phenotype of NTRK-fusion-positive tumors, including LPF-NTs (n=3), infantile fibrosarcoma-like tumor (n=2) and malignant peripheral nerve sheath tumor-like (n=1). Three cases showed coexpression of S100 and CD34, whereas the remaining 3 had a nonspecific immunoprofile. The tumors ranged morphologically and clinically from benign to highly malignant. None of the LPF-NT cases recurred, whereas 2 patients with malignant histology had a highly aggressive course with distant metastases to lung and other viscera. By targeted RNA sequencing these tumors harbored RET fusions with an identical break in exon 12, which retains the tyrosine kinase domain in the fusion oncoprotein and involving various gene partners (CLIP2, CCDC6, SPECC1L, MYH10, and NCOA4). Our results suggest that RET fusion-positive neoplasms share a similar phenotypic spectrum with the NTRK-positive tumors, displaying either fibroblastic or neural-like differentiation, and spanning a wide spectrum of clinical behavior. These findings open new avenues for targeted therapy with RET inhibitors currently available in clinical trials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".