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Record W2997634430 · doi:10.1111/nan.12590

Diffuse glioneuronal tumour with oligodendroglioma‐like features and nuclear clusters (DGONC) – a molecularly defined glioneuronal CNS tumour class displaying recurrent monosomy 14

2019· article· en· W2997634430 on OpenAlex
Maximilian Deng, Martin Sill, Dominik Sturm, Damian Stichel, Hendrik Witt, Jeff Ecker, Anja Wittmann, Jens Schittenhelm, Martin Ebinger, Martin U. Schuhmann, Dominique Figarella‐Branger, Eleonora Aronica, Ori Staszewski, Matthias Preusser, Christine Haberler, Melchior Lauten, Ulrich Schüller, Christian Hartmann, Matija Snuderl, Christopher Dunham, Nada Jabado, Pieter Wesseling, Martina Deckert, Kathy Keyvani, Nicholas G. Gottardo, Felice Giangaspero, Katja von Hoff, David W. Ellison, Torsten Pietsch, Christel Herold‐Mende, Till Milde, Olaf Witt, Marcel Kool, Andrey Korshunov, Wolfgang Wick, Andreas von Deimling, Stefan M. Pfister, David Jones, Felix Sahm

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNeuropathology and Applied Neurobiology · 2019
Typearticle
Languageen
FieldMedicine
TopicGlioma Diagnosis and Treatment
Canadian institutionsMcGill University Health CentreMcGill UniversityUniversity of British Columbia
FundersStichting Kinderen KankervrijDeutsche KrebshilfeElse Kröner-Fresenius-StiftungDeutsches KrebsforschungszentrumPediatric Brain Tumor FoundationPediatric Low Grade Astrocytoma FoundationBrain Tumour CharityIra Sohn Research Conference Foundation
KeywordsOligodendrogliomaPathologyMedicineGliomaAstrocytomaCancer research

Abstract

fetched live from OpenAlex

AIMS: DNA methylation-based central nervous system (CNS) tumour classification has identified numerous molecularly distinct tumour types, and clinically relevant subgroups among known CNS tumour entities that were previously thought to represent homogeneous diseases. Our study aimed at characterizing a novel, molecularly defined variant of glioneuronal CNS tumour. PATIENTS AND METHODS: DNA methylation profiling was performed using the Infinium MethylationEPIC or 450 k BeadChip arrays (Illumina) and analysed using the 'conumee' package in R computing environment. Additional gene panel sequencing was also performed. Tumour samples were collected at the German Cancer Research Centre (DKFZ) and provided by multinational collaborators. Histological sections were also collected and independently reviewed. RESULTS: Genome-wide DNA methylation data from >25 000 CNS tumours were screened for clusters separated from established DNA methylation classes, revealing a novel group comprising 31 tumours, mainly found in paediatric patients. This DNA methylation-defined variant of low-grade CNS tumours with glioneuronal differentiation displays recurrent monosomy 14, nuclear clusters within a morphology that is otherwise reminiscent of oligodendroglioma and other established entities with clear cell histology, and a lack of genetic alterations commonly observed in other (paediatric) glioneuronal entities. CONCLUSIONS: DNA methylation-based tumour classification is an objective method of assessing tumour origins, which may aid in diagnosis, especially for atypical cases. With increasing sample size, methylation analysis allows for the identification of rare, putative new tumour entities, which are currently not recognized by the WHO classification. Our study revealed the existence of a DNA methylation-defined class of low-grade glioneuronal tumours with recurrent monosomy 14, oligodendroglioma-like features and nuclear clusters.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.931
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
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 head0.007
GPT teacher head0.210
Teacher spread0.203 · 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