Primary de‐differentiated, trans‐differentiated and undifferentiated melanomas: overview of the clinicopathological, immunohistochemical and molecular spectrum
Bibliographic record
Abstract
Primary cutaneous and mucosal melanoma shows a wide histological spectrum. The correct diagnosis depends upon the demonstration of melanocytic differentiation by recognition of an associated in-situ component or immunohistochemical evidence of a melanocytic phenotype using conventional melanocytic markers, such as S-100, SOX10, Melan-A and HMB-45. Exceptionally, melanomas lose their melanocytic phenotype, at least focally, and show differentiation towards other lineages. Review of the literature shows that de- and trans-differentiation in melanoma is rare but probably under-recognised and under-reported. These often large and frequently ulcerated tumours affect adults and show a wide anatomical distribution, including mucosal sites, although there is a predilection for sun-damaged skin of the head and neck. Histologically, the tumours are biphasic and contain a pre-existing conventional melanoma. The de-differentiated component closely resembles atypical fibroxanthoma, both morphologically and immunohistochemically. Trans-differentiated melanoma may show rhabdomyosarcomatous or spindle cell carcinomatous features. Undifferentiated melanomas are similar tumours in which the conventional melanoma component is absent. Their diagnosis depends entirely upon the clinical context and identification of a classical melanoma driver gene mutation, i.e. BRAF V600E. The diagnosis of these rare and unusual tumours is challenging, and requires thorough tumour sampling and recognition of the background of a pre-existing but often focal conventional melanoma together with molecular analysis.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".