Assessing targetable NTRK1/2/3 fusions in mesenchymal tumors via whole-exome RNA sequencing
Bibliographic record
Abstract
BACKGROUND: Neurotrophic receptor tyrosine kinase (NTRK) 1/2/3 fusions, though rare, are highly sought in cancer diagnostics due to tyrosine kinase inhibitors' histology-agnostic approval based on significant efficacy across tumor types. In mesenchymal tumors, these fusions are identified in five typical NTRK-rearranged mesenchymal tumors (NMT): infantile fibrosarcomas, lipofibromatosis-like neural tumors, NTRK-rearranged spindle cell neoplasms, and minority subsets of ALK-negative inflammatory myofibroblastic tumors and quadruple wild-type gastrointestinal stromal tumors. However, their occurrence in other subtypes and actionability remain uncertain. METHODS: This retrospective study included adult and pediatric patients with mesenchymal FFPE (formalin-fixed, paraffin-embedded) tumor samples collected between January 2016 and March 2023. Eligible samples underwent whole-exome RNA sequencing (WERS) for mesenchymal tumor diagnosis or theranostic assessment. Results were reviewed by a multidisciplinary molecular board to assess technical, biological, and clinical relevance. RESULTS: Among 3015 samples, primarily malignant, intermediate, and benign mesenchymal tumors, 111 (3.68%) harbored at least one bioinformatically detected NTRK fusion. Forty-three were biologically irrelevant due to absent kinase domains (group 1), and 11 were technical false positives (group 2). Of the 57 robustly identified cases (1.8%), 54 were typical NMT subtypes with canonical gene partners (group 3). Group 4 included three rare fusions in genetically complex sarcomas: MDM2/CDK4-amplified liposarcoma, MDM2/CDK4-amplified intimal sarcoma, and uterine leiomyosarcoma. These cases featured novel fusion partners, higher fusion counts, and comparable single nucleotide variants (SNVs) to group 3. CONCLUSION: WERS reliably identifies actionable NTRK fusions, predominantly in five NMT subtypes, whereas NTRK fusions were rare and extremely rare in other sarcomas where their targetability remains unclear. Routine NTRK screening should prioritize tumors suspected of being NMT rather than being broadly applied.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".