What the EWSR1-ATF1 Fusion has Taught Us About Hyalinizing Clear Cell Carcinoma
Bibliographic record
Abstract
Hyalinizing clear cell carcinoma (HCCC) is a unique low-grade tumor composed of cords and nests of clear cells in a hyalinized stroma that was first reported by Milchgrub et al. It was recognized as a separate entity from clear cell variants of epithelial-myoepithelial carcinoma, myoepithelial carcinoma and mucoepidermoid carcinoma. HCCC is included in a long list of clear cell-containing tumors of salivary gland, as well as odontogenic tumors and metastases (renal cell carcinoma). Up until now, it has been considered a diagnosis of exclusion, despite its very distinctive appearance, and labeled as "not otherwise specified" by the World Health Organization. The emergence of molecular data in salivary gland tumors, including HCCC now allow for a more rigorous appraisal of its spectrum. The EWSR1-ATF1 fusion has proven the concept of a "mucinous HCCC" and removes mucin as an exclusion criterion for this tumor. It has also proven a genetic link between clear cell odontogenic carcinoma and HCCC. Molecularly-proven cases have also highlighted variant morphologies and shown that cases with overt squamous differentiation are true HCCC. This gives further weight to the classification of this tumor as squamous or adenosquamous in differentiation and as a specific entity rather than an "NOS" tumor.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".