Expanding the spectrum of AFF2 carcinoma: clinical, morphological, immunohistochemical, and molecular characteristics of five cases harboring alternate fusions
Bibliographic record
Abstract
In recent years, multiple molecularly defined entities have emerged in head and neck pathology, especially among sinonasal squamous and basaloid carcinomas, including NUT carcinoma, SWI/SNF-deficient carcinoma, and DEK::AFF2 carcinoma. These tumors show significant morphological and immunophenotypic diversity. We present five novel head and neck carcinomas harboring AFF2 rearrangements involving previously unreported fusion partners. Five cases (3 males, 2 females; ages 35-72 years) presented with tumors in the sinonasal region (n = 4) and parotid gland (n = 1), measuring between 3.3 and 6.3 cm. RNA sequencing identified fusions involving AFF2 with H3-3A, EWSR1, CHD4 (two cases: neck lymph node metastasis, which turned out to be sinonasal primary and parotid mass), and NUCKS1. Tumors harboring H3-3A::AFF2 and NUCKS1::AFF2 fusions exhibited bland transitional cell-like morphology with acantholytic changes similar to classic DEK::AFF2 carcinoma; the NUCKS1 fusion also demonstrated clear cell features. In contrast, the EWSR1::AFF2 fusion tumor showed high-grade adenocarcinoma morphology with focal neuroendocrine marker expression, lacking p63 and CK5/6. The two CHD4::AFF2 fusion cases demonstrated neuroendocrine differentiation; one was a cytokeratin-negative small blue round cell carcinoma, and the other showed mixed squamoid-neuroendocrine features with strong cytokeratin and p63 expression. All tumors demonstrated consistent AFF2 immunoreactivity. These findings suggest that AFF2-rearranged tumors form a spectrum of carcinomas with diverse morphologies, immunophenotypes, and differentiation patterns. Given the consistent involvement of the AFF2 gene and uniform AFF2 immunohistochemical positivity despite morphological heterogeneity, we propose naming this entity AFF2 carcinoma.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".