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Record W4200313113 · doi:10.1136/jclinpath-2021-207952

BAP1-deficient meningioma presenting with trabecular architecture and cytokeratin expression: a report of two cases and review of the literature

2021· review· en· W4200313113 on OpenAlexaff
Alexander Landry, Justin Z. Wang, Farshad Nassiri, Vikas Patil, Andrew Gao, Gelareh Zadeh

Bibliographic record

VenueJournal of Clinical Pathology · 2021
Typereview
Languageen
FieldMedicine
TopicMeningioma and schwannoma management
Canadian institutionsUniversity Health NetworkPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsBAP1MeningiomaPathologyCancer researchMedicineImmunohistochemistryBiologyMelanoma

Abstract

fetched live from OpenAlex

AIMS: gene, a tumour suppressor that is lost in several cancers. Importantly, such mutations have been shown to be susceptible to poly (ADP-ribose) polymerase (PARP) inhibition in preclinical studies, offering hope for targeted therapy. While rare, BAP1 loss has been observed in a subset of rhabdoid and papillary meningioma and is associated with earlier recurrence. We seek to add to the literature on this rare disease and advocate for more routine BAP1 testing. METHODS: We present a report of two cases of BAP1-deficient meningioma and review the available literature on this rare entity. RESULTS: Both cases present with a distinct trabecular architecture without rhabdoid or papillary features. Interestingly, both also presented with radiographic and histopathological findings unusual for meningioma. While immunohistochemistry and genetic sequencing confirmed BAP1 loss, DNA methylation analysis was required to confirm the final diagnosis. CONCLUSIONS: We suggest that BAP1-deficient meningioma should be considered in the differential diagnosis of extra-axial central nervous system (CNS) tumours with atypical imaging or histopathological features and that BAP1 loss may constitute a clinically important meningioma subtype with opportunities for targeted therapy.

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.337
Threshold uncertainty score0.571

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.085
GPT teacher head0.436
Teacher spread0.351 · 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 designCase report
Domainnot available
GenreReview

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

Citations9
Published2021
Admission routes1
Has abstractyes

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