TLE1 as a Diagnostic Immunohistochemical Marker for Synovial Sarcoma Emerging From Gene Expression Profiling Studies
Bibliographic record
Abstract
Synovial sarcoma is a soft tissue malignancy defined by the SYT-SSX fusion oncogene. Demonstration of the t(X;18) by cytogenetics, fluorescence in situ hybridization or reverse-transcriptase polymerase chain reaction has become the gold standard for diagnosis, but practical considerations limit the availability of these methods. Gene expression profiling studies performed by several independent groups have consistently identified TLE1 as an excellent discriminator of synovial sarcoma from other sarcomas, including histologically similar tumors such as malignant peripheral nerve sheath tumor. TLE proteins (human homologues of Groucho) are transcriptional corepressors that inhibit Wnt signaling and other cell fate determination signals, and so have an established role in repressing differentiation. We examined the expression of TLE proteins in synovial sarcoma and in a broad range of mesenchymal tumors using tissue microarrays to assess the value of anti-TLE antibodies in the immunohistochemical confirmation of synovial sarcoma. We demonstrate that TLE expression is a consistent feature of synovial sarcoma using both a well-characterized monoclonal antibody recognizing the TLE family of proteins and a commercially available polyclonal antibody raised against TLE1. Both antibodies gave intense and/or diffuse nuclear staining in 91/94 molecularly confirmed synovial sarcomas. Moderate staining is occasionally seen in schwannoma and solitary fibrous tumor/hemangiopericytoma. In contrast, TLE staining is detected much less frequently and at lower levels, if at all, in 40 other mesenchymal tumors. Our findings establish TLE as a robust immunohistochemical marker for synovial sarcoma, and may have implications for understanding the biology of synovial sarcoma and for developing experimental therapies for this cancer.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".