MétaCan
Menu
Back to cohort
Record W4392813852 · doi:10.1111/cup.14602

Primary cutaneous <scp>NUT</scp> carcinoma with <i>BRD4::NUTM1</i> fusion

2024· article· en· W4392813852 on OpenAlexaff
Ahmed Shah, Adrian Box, Thomas Brenn, Ashley Flaman

Bibliographic record

VenueJournal of Cutaneous Pathology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Degradation and Inhibitors
Canadian institutionsCalgary Laboratory ServicesUniversity of Calgary
Fundersnot available
KeywordsNuclear atypiaPathologyCarcinomaMedicineMalignancyBiopsyAtypiaBRD4BiologyImmunohistochemistryBromodomain

Abstract

fetched live from OpenAlex

Nuclear protein in testis (NUT) carcinoma, molecularly defined by the NUTM1 gene rearrangement, is most commonly reported in young adults in the sinonasal tract, nasopharynx, or thorax. At these sites, NUT carcinoma is an extremely aggressive malignancy with dismal prognosis. Recently, five cases of primary cutaneous NUT adnexal carcinoma have been reported with BRD3 and NSD3 fusion partners. Although NUT adnexal carcinomas are shown to have metastatic potential, they may behave less aggressively than extracutaneous NUT carcinomas. We report a case of a 59-year-old man who underwent a biopsy of a 3-cm plantar mass, which showed BRD4::NUTM1 fusion. The tumor was a poorly differentiated dermal neoplasm showing cytologic atypia, large vesicular nuclei with prominent nucleoli, conspicuous mitotic activity, and foci of necrosis. Immunohistochemically, the tumor showed positivity for keratins, EMA, SOX10, and NUT, with patchy smooth muscle actin. Molecular testing revealed BRD4::NUTM1 rearrangement. With no alternative primary identified by imaging, a diagnosis of primary cutaneous NUT carcinoma was favored. We hope to contribute to the limited body of knowledge on this entity, with emphasis on recognition as well as studying and defining its prognostic differences from extracutaneous NUT carcinomas.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.677
Threshold uncertainty score0.791

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.005
GPT teacher head0.210
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations7
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Cutaneous PathologySame topicProtein Degradation and InhibitorsFrench-language works237,207