FLI-1 Distinguishes Ewing Sarcoma From Small Cell Osteosarcoma and Mesenchymal Chondrosarcoma
Bibliographic record
Abstract
Small cell osteosarcoma and mesenchymal chondrosarcoma are 2 primary bone tumors with a small round blue cell component, which can mimic the appearance of Ewing sarcoma. Distinguishing these tumors from each other on biopsy material is important clinically, as optimal therapy differs according to the tumor type. However, separating these entities on morphology alone can be challenging. FLI-1 has been described to be a useful marker for Ewing sarcoma, particularly when hematolymphoid markers are negative. In small cell osteosarcoma and mesenchymal chondrosarcoma, the FLI-1 staining pattern has not been adequately characterized. Using a monoclonal FLI-1 antibody, nuclear immunoreactivity in tumor cells was evaluated in 10 small cell osteosarcomas, 10 mesenchymal chondrosarcomas, and 8 Ewing sarcomas, together with a number of other small, round, blue cell tumors. None of the small cell osteosarcomas or mesenchymal chondrosarcomas exhibited FLI-1 staining in the tumor cells, in contrast to the positive nuclear FLI-1 staining in the stromal endothelial cells. In comparison, 6 of the 8 Ewing sarcomas showed moderate-to-strong nuclear FLI-1 staining of the tumor cells in addition to strong staining of the stromal endothelial cell nuclei. With the exception of lymphoblastic lymphomas, FLI-1 positivity was not seen in the other small round blue cell tumors examined. These findings show that, in contrast to Ewing sarcoma, small cell osteosarcoma and mesenchymal chondrosarcoma lack FLI-1 immunoreactivity. FLI-1 is therefore useful in the differential diagnosis of small round blue cell tumors of the bone.
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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) | 0.000 | 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 | 0.000 | 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".