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Record W2979457044 · doi:10.1002/gcc.22814

Novel <i>SS18‐NEDD4</i> gene fusion in a primary renal synovial sarcoma

2019· article· en· W2979457044 on OpenAlexaff
Pedram Argani, Lei Zhang, Yun‐Shao Sung, Carlos E. Bacchi, David Swanson, Brendan C. Dickson, Cristina R. Antonescu

Bibliographic record

VenueGenes Chromosomes and Cancer · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRenal and related cancers
Canadian institutionsMount Sinai Hospital
FundersNational Cancer Institute
KeywordsSynovial sarcomaFusion geneGeneNEDD4MedicineBiologyCancer researchSarcomaPathologyGeneticsUbiquitin

Abstract

fetched live from OpenAlex

We report a primary renal synovial sarcoma with a novel gene fusion and unusual morphology. The patient was a 35-year-old female who was found to have a 5 cm hypocellular, myxoid spindle cell renal neoplasm that subtly permeated amongst native renal tubules. The tumor cells showed elongated hyperchromatic nuclei with ill-defined pale cytoplasm, lacking significant mitotic activity or necrosis. Based on its deceptively bland morphology, the differential diagnosis included mainly benign entities, such as metanephric stromal tumor, mixed epithelial stromal tumor (MEST), and myxoid peripheral nerve sheath tumors. A definitive diagnosis of synovial sarcoma was made only subsequently to RNA-sequencing, which revealed a novel SS18-NEDD4 gene fusion. These results were further confirmed by fluorescence in situ hybridization using custom design break-apart probes for both genes. This case illustrates the utility of targeted RNA-sequencing in the classification of challenging tumors with deceptive morphology and identification of novel gene fusion variants. Apart from the canonical SS18-SSX fusion, this is only the second alternative gene fusion variant described in synovial sarcoma to date, in addition to two cases harboring the SS18L1-SSX1 fusion.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.250
Threshold uncertainty score0.586

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 head0.214
Teacher spread0.209 · 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

Citations21
Published2019
Admission routes1
Has abstractyes

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