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Record W4232086884 · doi:10.1093/neuonc/now212.452

MPTH-14. MOLECULAR CLASSIFICATION AND CLINICAL CHARACTERISTICS OF MEDULLOBLASTOMAS IN JAPAN

2016· article· en· W4232086884 on OpenAlexaff
Yonehiro Kanemura, Tomoko Shofuda, Koichi Ichimura, Ema Yoshioka, Daisuke Kanematsu, Mami Yamasaki, Soichiro Shibui, Hajime Arai, Michael D. Taylor, Hiroaki Sakamoto, Ryo Nishikawa

Bibliographic record

VenueNeuro-Oncology · 2016
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsWnt signaling pathwayMedulloblastomaCytogeneticsImmunohistochemistryMolecular geneticsOncologyBiologyPhenotypeInternal medicineMolecular cytogeneticsGeneCancer researchPathologyBioinformaticsMedicineGeneticsChromosome

Abstract

fetched live from OpenAlex

Resent intensive genomic and molecular biological analyses of medulloblastomas have revealed that they are at least classified into four core subgroups: WNT, SHH, Group 3, and Group 4 based on difference in cytogenetics, mutational spectra, and gene expression signatures, as well as in clinical phenotypes and outcomes. This four-subgroup system of medulloblastomas will become not only a novel prognostic marker but also lead to improved diagnosis and risk stratification systems in combination with metastatic, cytogenetics, and or mutational statuses. To deal with this progress, we have founded the Japanese Pediatric Molecular Neuro-oncology Group (JPMNG) and initiated a clinical research project to establish a nationwide network of a molecular diagnosis system for pediatric brain tumors in Japan. Fresh-frozen and/or formalin-fixed paraffin-embedded archived tissue specimens are collected. Diagnostic methods have been optimized to reliably and reproducibly classify them into molecular subgroups according to the consensus criteria. These include gene expression analysis using the NanoString nCounter system, immunohistochemistry, and DNA sequencing. We have so far collected a total of 190 medulloblastomas from 37 hospitals. An analysis using 149 meduloblastomas indicated that proportions of four core subgroups were WNT (12.1%), SHH (28.9%), Group 3 (15.4%) and Group 4 (43.6%), respectively. The frequencies of Group3 are lower and Group 4 is higher than those of published results. CTNNB1 mutations were found in 88.9% of WNT, and TP53 mutations were identified in 17.6% of WNT and 24.3% of SHH, and 1.7% of Group 4. Mutation of TERT promoter was also found in 5 SHH tumors. Prognosis of WNT/SHH was very good, while Group 3 showed the poorest prognosis of all 4 subgroups median survival time being 22.9 months. The JPMNG project will thus improve the molecular diagnosis of pediatric brain tumors, leading to more appropriate treatment choice and better clinical outcomes in Japan.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.034
GPT teacher head0.342
Teacher spread0.308 · 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
Published2016
Admission routes1
Has abstractyes

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