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Microarray-based DNA methylation profiles of primary medulloblastomas

GSE93646 Homo sapiens (human) DNA methylation 428 samples Submitted 2017/05/29 Platform GPL13534
At a glance

DNA methylation · human · 428 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Homo sapiens (human)
Topic
MedulloblastomaThis series is part of our curated briefing on it.
Samples
428 samples: 398 × genomic DNA from medulloblastoma_NMB vs 2 × genomic DNA from medulloblastoma_PNETGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI.
Summary (written by the submitters)
Identification of novel molecular subgroups Background: International consensus recognises four medulloblastoma molecular subgroups - WNT, SHH, Group 3 and Group 4 - each defined by their characteristic genome-wide transcriptomic and DNA methylomic profiles. Subgroups harbor distinct clinico-pathological and molecular features, underpin current disease sub-classification and initial subgroup-directed therapies are underway in clinical trials (i.e.
Read the full summary ↓
reduced risk-adapted treatments for favorable-risk WNT patients; SMO inhibitors for SHH patients). However, significant biological heterogeneity and differences in survival are apparent within each subgroup, which remain to be resolved. Methods: We undertook comprehensive molecular profiling and unsupervised class discovery (non-negative matrix factorization, t-SNE) of test and validation cohorts to identify consensus primary molecular subgroups within childhood medulloblastoma (<16.0 years), and characterize their clinical and biological significance. Survival modeling was performed in clinically-annotated centrally-reviewed patients (>3.0 years). Findings: Seven robust and reproducible primary molecular subgroups of childhood medulloblastoma were identified, characterized by distinct biological/clinical features. For instance, SHH comprised two age-dependent subgroups, while Grp3 and Grp4 each split into two subgroups with significantly different survival rates. Survival analysis identified secondary features predictive of outcome. Cross-validated subgroup-dependent models incorporating these novel subgroups along with secondary features and established disease risk-factors, outperformed current disease risk-stratification schemes. These schema stratified patients into four clinical risk-groups - favorable-risk (91% 5-year survival, 25% of patients), standard-risk (81%, 23%), high-risk (42%, 38%) and very high-risk (28%, 13%) - to be considered for treatment reduction, intensification or novel therapies respectively. Interpretation: The discovery of seven novel, clinically-significant, subgroups significantly improves disease risk-stratification and provides a new foundation for future research and clinical investigations.
This dataset
Open GSE93646 in finder → Find more human methylation datasets → Medulloblastoma landscape →
Download · which file do I need?

Direct links to NCBI, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need.

All supplementary files ↗
3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE93646_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

What the files usually look like: Look for beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA361460. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 28545823) ↗
Study design
398 × genomic DNA from medulloblastoma_NMB vs 2 × genomic DNA from medulloblastoma_PNET

Supports a between-group comparison across 400 samples.

How we read this: 2 replicated groups read from the first 400 of 428 sample titles; they account for 400 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 388 more — browse all 428 samples with per-sample file links →

More Medulloblastoma datasets

Search all human methylation datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.