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Record W2617029719 · doi:10.1093/neuonc/nox083.065

EPND-07. MOLECULAR HETEROGENEITY AMONG PEDIATRIC POSTERIOR FOSSA EPENDYMOMA

2017· article· en· W2617029719 on OpenAlexaff
Kristian W. Pajtler, Ji Wen, Martin Sill, Tong Lin, Jens M Hübner, Vijay Ramaswamy, Chandanamali Punchihewa, David Jones, Hendrik Witt, Lukas Chávez, Ruth Tatevossian, Richard G. Grundy, Thomas E. Merchant, Michael D. Taylor, Stefan M. Pfister, Andrey Korshunov, Marcel Kool, David W. Ellison

Bibliographic record

VenueNeuro-Oncology · 2017
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsEpendymomaBiologyGenetic heterogeneityMedulloblastomaGeneHistogenesisDiseaseGenomeGeneticsBioinformaticsPathologyOncologyImmunohistochemistryMedicineImmunology

Abstract

fetched live from OpenAlex

Previously, we have identified nine distinct molecular groups of ependymoma across all age groups, three in each major anatomical compartment of the CNS: spinal, posterior fossa, and supratentorial. These nine molecular groups are genetically, epigenetically, transcriptionally, demographically, and clinically distinct. Pediatric intracranial ependymomas are either affiliated with the RELA and YAP1 supratentorial groups or with the posterior fossa PFA group. RELA and YAP1 ependymomas harbor recurrent and distinct fusion genes that drive the disease, but PFA ependymomas lack significant recurrent mutations, and the specific oncogenic events underlying these tumors remain undefined. Observing distinct outcomes among children with PFA ependymomas, we tested the hypothesis that further molecular diversity with clinical utility, including possible novel genetic alterations, may exist among these tumors. Genome-wide DNA methylation profiles of 681 pediatric PFA ependymomas were analyzed by unsupervised consensus hierarchical clustering and t-distributed stochastic neighbor embedding (tsne), which identified not only three major distinct molecular subgroups of PFA ependymoma: PFA-1, PFA-2, and PFA-3, but additional small subgroups that segregate within PFA-1 and PFA-2. Subgroups were characterized by distinct clinical and genetic characteristics; most PFA-3 tumors harbored 1q gain and occurred in children significantly older than those with PFA-1 and PFA-2 tumors. Some of the small subgroups demonstrated distinctive copy number alterations or gene mutations, e.g. H3 K27M. Outcome data revealed considerable heterogeneity among the different subgroups, overall survival at 5 years was >90% for one subgroup, but <20% for two others. We conclude that further molecular refinement of pediatric PFA ependymomas has clinical utility and the potential for enhanced risk assessment or therapeutic stratification. In addition, identification of PFA subgroups and further molecular heterogeneity within these subgroups may help to identify the drivers of PFA ependymomas.

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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.025
GPT teacher head0.319
Teacher spread0.293 · 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
Published2017
Admission routes1
Has abstractyes

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