Emerging fusion-associated mesenchymal tumours: a tabular guide and appraisal of five ‘novel’ entities
Bibliographic record
Abstract
Aims The field of molecular pathology has undergone significant advancements in the clinical impact of sarcoma diagnosis, resulting in challenges to nosology of bone and soft tissue tumours. The surge in molecular data has led to the identification of novel fusions and description of new ‘entities’. To illustrate this, we have selected five emerging entities with novel fusions: clear cell stromal tumour of the lung with YAP1::TFE3 fusion, GAB1::ABL1 fusion spindle cell neoplasm, NUTM1 -rearranged sarcomas, NR1D1 -rearranged sarcomas and calcified chondroid mesenchymal neoplasms. Methods Literature for the relevant case reports and case series of these five entities were reviewed and clinicopathological data was collected. Additionally, this review includes a table format of recently described fusion-associated mesenchymal neoplasms. Results The morphological and immunohistochemical features, along with diagnostic challenges, are discussed for each entity. Conclusions Here, we have provided a review of selected emerging mesenchymal neoplasms, which of these neoplasms will meet the threshold to be ‘new entities’ remains to be determined.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".