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Record W4399785510 · doi:10.1093/neuonc/noae064.520

MDB-71. IDENTIFICATION AND DESCRIPTION OF A NOVEL TYPE OF MEDULLOBLASTOMA

2024· article· en· W4399785510 on OpenAlexaff
Alicia Eckhardt, Chris Meulenbroeks, Neal Geisemeyer, Michael Bockmayr, Karoline Hack, Marthe Sönksen, Christian Thomas, Melanie Schoof, Arend Koch, Sage Green, David Doss, Ekin Güney, Arie Perry, Stephan Frank, Peter Kuzman, Miriam Ratliff, Abigail K. Suwala, Stefan Rutkowski, Martin Hasselblatt, Michael D. Taylor, David Jones, Marcel Kool, Ulrich Schüller

Bibliographic record

VenueNeuro-Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsSickKids FoundationHospital for Sick Children
Fundersnot available
KeywordsMedulloblastomaIdentification (biology)Type (biology)Computer scienceMedicineBiologyPathology

Abstract

fetched live from OpenAlex

Abstract BACKGROUND Medulloblastoma (MB) is one of the most frequent high-grade brain tumor types of childhood and adolescence. Based on biology, histology, and its clinical course, MB is a heterogeneous disease with four different molecular types (WNT, SHH, Group 3, and Group 4), which are most reliably distinguishable by their global DNA methylation pattern. METHODS We analyzed DNA methylation (n=47), copy number variants, transcriptomic data (n=7) and histology (n=28) of a previously unrecognized type of MB. RESULTS As a result of integrating DNA methylation data of >2,600 MB and screening of >140,000 data sets uploaded to the DKFZ brain tumor classifier (www.molecularneuropathology.org), we identified a small group of MB that displayed a homogeneous DNA methylation pattern, which was clearly distinct from previously known MB types. Tumors within this group have also been recognized as a separate methylation class by latest versions of the classifier, which has provisionally been named medullomyoblastoma (MB_MYO). Transcriptomic data were similarly distinct from other MB types. Comparison of these data to various cell types of the developing hindbrain revealed transcriptional similarities to precursor cells of the rhombic lip with signatures of WNT signaling and myogenic differentiation. In line with the latter findings, 2/11 cases with DNA sequencing data harbored hotspot CTNNB1 mutations and 5/28 cases showed a myogenic differentiation based on histology. MYC amplifications were present in 11/47 cases, corresponding to a higher fraction of MYC-amplified tumors compared to all known MB types. Median age at diagnosis in this cohort was 16 years, and five-year overall survival was ~75 %. CONCLUSIONS In summary, we describe a novel type of MB identified by DNA methylation profiling that likely needs to be addressed separately during the retrospective analyses of MB patient cohorts, for the design of future clinical trials, and when evaluating targeted therapies.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.050
GPT teacher head0.330
Teacher spread0.281 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2024
Admission routes1
Has abstractyes

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