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Record W2333308044 · doi:10.1093/neuonc/nou254.9

EG-09 * EPIGENETIC PROFILING REVEALS A CpG HYPERMETHYLATION PHENOTYPE (CIMP) ASSOCIATED WITH WORSE PROGRESSION-FREE SURVIVAL IN MENINGIOMA

2014· article· en· W2333308044 on OpenAlexaff
Adriana Olar, Khalida Wani, Alireza Mansouri, Gelareh Zadeh, Clark A. Wilson, Franco DeMonte, Gregory N. Fuller, David Jones, Stefan M. Pfister, Andreas von Deimling, Erik P. Sulman, K. Aldape

Bibliographic record

VenueNeuro-Oncology · 2014
Typearticle
Languageen
FieldMedicine
TopicGestational Trophoblastic Disease Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDNA methylationEpigeneticsMethylationPhenotypeBiologyCpG siteComputational biologyOncologyInternal medicineMedicineGeneticsGeneGene expression

Abstract

fetched live from OpenAlex

BACKGROUND: Methylation profiling of solid tumors has revealed biologic subtypes, often with clinical implications. Methylation profiles of meningioma and their clinical implications are not well understood. METHODS: Ninety-two meningioma samples (n = 44 test set and n = 48 validation set) were profiled using the Illumina HumanMethylation450 BeadChip. Unsupervised clustering and analyses for recurrence-free survival (RFS) were performed. RESULTS: Unsupervised clustering of the test set using approximately 900 highly variable markers identified two clearly defined methylation subgroups. One of the groups (n = 19) showed global hypermethylation of a set of markers, analogous to CpG island methylator phenotype (CIMP). These findings were reproducible in the validation set, with 18/48 samples showing the CIMP-positive phenotype. Importantly, of 347 highly variable markers common to both the test and validation set analyses, 107 defined CIMP in the test set and 94 defined CIMP in the validation set, with an overlap of 83 markers between the two datasets. This number is much greater than expected by chance indicating reproducibly of the hypermethylated markers that define CIMP in meningioma. With respect to clinical correlation, the 37 CIMP-positive cases displayed significantly shorter RFS compared to the 55 non-CIMP cases (hazard ratio 2.9, p = 0.013). In an effort to develop a preliminary outcome predictor, a 155-marker subset correlated with RFS was identified in the test dataset. When interrogated in the validation dataset, this 155-marker subset showed a statistical trend (p < 0.1) towards distinguishing survival groups. CONCLUSIONS: This study defines the existence of a CIMP phenotype in meningioma, which involves a substantial proportion (37/92, 40%) of samples with clinical implications. Ongoing work will expand this cohort and examine identification of additional biologic differences (mutational and DNA copy number analysis) to further characterize the aberrant methylation subtype in meningioma. CIMP-positivity with aberrant methylation in recurrent/malignant meningioma suggests a potential therapeutic target for clinically aggressive cases.

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)0.008
Version: codex-gemma-dda1882f352aValidation 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 score0.239
Threshold uncertainty score0.904

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.024
GPT teacher head0.310
Teacher spread0.286 · 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.

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
Published2014
Admission routes1
Has abstractyes

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