Fine needle aspiration biopsy diagnosis of dedifferentiated liposarcoma: Cytomorphology and MDM2 amplification by FISH
Bibliographic record
Abstract
Lipomatous mesenchymal tumors constitute the most common type of soft tissue tumors. Well-differentiated liposarcoma (WDLS) can undergo dedifferentiation to a nonlipogenic sarcoma of variable histologic grade. In the recent literature, amplification of the murine double minute 2 (MDM2) oncogene, which has a role in cell cycle control, has been successful in distinguishing WDLS from benign lesions. We present a case of dedifferentiated liposarcoma diagnosed by fine-needle aspiration (FNA), using cytomorphology and ancillary studies (immunocytochemistry and fluorescent in-situ hybridization). An 85-year old female presented to our institution with a firm soft tissue mass of the right buttock. The FNA showed atypical spindle cells, osteoclast-like giant cells and extracellular dense matrix material. The cell block showed cellular groups of highly atypical spindle cells with osteoid and adipose tissue. Fluorescence in situ hybridization (FISH) studies performed on the cell block demonstrated amplification of the MDM2 gene. In addition, the findings were morphologically compatible with the previously resected retroperitoneal dedifferentiated liposarcoma with areas of osteosarcoma. This rare case illustrates the usefulness of FNA and ancillary studies in the diagnosis and subclassification of soft tissue tumors. To the best of our knowledge, this is the first report of MDM2 FISH positivity in a liposarcoma diagnosed by FNA.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".