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Record W4399786782 · doi:10.1093/neuonc/noae064.512

MDB-63. AN INTERNATIONAL META-ANALYSIS OF SHH MEDULLOBLASTOMA SUBTYPES DEFINES A CLINICALLY SIGNIFICANT HIGH-RISK VARIANT OF SHH-SUBTYPE 3

2024· article· en· W4399786782 on OpenAlexaff
Ed C. Schwalbe, Martin Sill, Hiro Suzuki, Frédéric Charron, Michael D. Taylor, Stefan M. Pfister, Steven C. Clifford

Bibliographic record

VenueNeuro-Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsSickKids FoundationHospital for Sick ChildrenMontreal Clinical Research Institute
Fundersnot available
KeywordsMedulloblastomaMeta-analysisOncologyInternal medicineMedicineCancer researchBiology

Abstract

fetched live from OpenAlex

Abstract BACKGROUND The distinction of MBSHH into four methylation-dependent subgroups was recognized by the WHO in 2021. However, these subgroups have not previously been defined by international experimental consensus and their clinico-molecular features and behavior have not formally been investigated in large cohorts. We aimed to robustly identify SHH subgroups through analysis of MBSHH with DNA-methylation profiling. METHODS A cohort of 683 MBSHH, confidently classified using the Heidelberg classifier v12.5, was assembled for analysis from multiple international studies. To define subgroups, we applied consensus sampling-based clustering approaches to tumor methylomes, including assessment of confidence in class-definition and inter-technique concordance. The clinico-molecular features of consensus subgroups were investigated. RESULTS Lowest complexity analysis supported the division of MBSHH into the 4 WHO-subtypes. SHH-1 and SHH-2 were associated with lower age and infrequent mutations of PTCH1/SUFU; SHH-2 was distinguished from SHH-1 by enriched MBEN histology, absence of chromosome 2 gain, less frequent metastasis and more favorable overall-survival. SHH-4 presented in older children and adults (3-57; median 24 years), and was primarily defined by mutations in U1-snRNA (67/72). Consensus analyses supported the division of SHH-subgroup-3 into three. Importantly, the SHH-3C subtype was associated with a coalescence of high-risk features (LCA histology, TP53mut, MYCNamp/GLI2amp) alongside 3p, 10q and 17p loss, and had dismal survival. The remaining SHH-3A/B subtypes were characterized by 9q loss, frequent focal amplifications of TERT and PPM1D, and equivalent better survival. CONCLUSIONS This study affirms the distinction of MBSHH into 4 major subgroups. For infant disease, SHH-2 is a favorable-risk marker. For childhood-MBSHH, the SHH-3C subtype provides a molecular definition of high-risk that subsumes other previously-defined high-risk disease markers (LCA, MYCNamp, TP53mut) into a unified high-risk disease group. The other SHH-3 subtypes behave similarly and are favorable-risk. These subtypes have potential to enhance molecularly-guided risk-stratification in routine diagnostics, to improve patient outcomes and quality-of-life.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.248
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.054
GPT teacher head0.353
Teacher spread0.298 · 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.

Study designMeta-analysis
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

Citations1
Published2024
Admission routes1
Has abstractyes

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