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Record W3087070372 · doi:10.1002/gcc.22897

A novel low‐grade nasopharyngeal adenocarcinoma characterized by a <i>GOLGB1‐BRAF</i> fusion gene

2020· article· en· W3087070372 on OpenAlexaff
Justin Bubola, Cristina R. Antonescu, Ilan Weinreb, David Swanson, John R. de Almeida, Christina MacMillan, Brendan C. Dickson

Bibliographic record

VenueGenes Chromosomes and Cancer · 2020
Typearticle
Languageen
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsUniversity Health NetworkUniversity of TorontoMount Sinai Hospital
FundersNational Cancer Institute
KeywordsFusion geneNasopharyngeal carcinomaCancer researchGeneOncologyMedicineBiologyInternal medicineComputational biologyGeneticsRadiation therapy

Abstract

fetched live from OpenAlex

Nasopharyngeal adenocarcinoma is a rare malignancy that is classified into conventional/surface- and salivary-types. Herein we report the case of a 52-year-old male who presented with a right nasopharyngeal mass and right-sided hearing loss. Diagnostic imaging revealed a circumscribed 1.7 cm mass centred in the right antero-lateral aspect of the nasopharynx. A biopsy showed a gland-forming neoplasm that was in continuity with the surface epithelium. The tumor exhibited a nested to micro-papillary architecture, with mild cytologic atypia. Immunohistochemistry demonstrated diffuse staining for CK7, SOX10, and p16; the abluminal layer was highlighted by CK5 and p63, while the luminal cells expressed CD117. The tumor was not amenable to subclassification and was diagnosed as a low-grade nasopharyngeal adenocarcinoma, not otherwise specified (NOS). Subsequent RNA sequencing was performed which identified a novel GOLGB1-BRAF fusion product. Based on its unique morphology and molecular findings, this is presumed to represent a novel subtype of nasopharyngeal adenocarcinoma. In addition to being of diagnostic relevance, this fusion may ultimately represent a potential therapeutic target.

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 score0.180
Threshold uncertainty score0.899

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.024
GPT teacher head0.257
Teacher spread0.233 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

Explore more

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