GEO series
Chromatin structure predicts survival in glioma patients
GSE295378
Homo sapiens (human)
ChIP-seq / ATAC-seq (genome binding and open chromatin)
38 samples
Submitted 2025/04/27
Platform GPL30173Platform GPL18573
At a glance
ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 38 samples
- What it is
- ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
- Organism
- Homo sapiens (human)
- Samples
- 38 samples: 38 samples, each with a distinct title — no replicated groupsGroups 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; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
The pathological changes in epigenetics and gene regulation that accompany the progression of low-grade to high-grade gliomas are under-studied. The authors use a large set of paired atac-seq and RNA-seq data from surgically resected glioma specimens to infer gene regulatory relationships in glioma. Thirty-eight glioma patient samples underwent atac-seq sequencing and 16 samples underwent additional RNA-seq analysis.
Read the full summary ↓
Using an atac-seq/RNA-seq correlation matrix, atac-seq peaks were paired with genes based on high correlation values (|r2| > 0.6). Samples clustered by IDH1 status but not by grade. Surprisingly there was a trend for IDH1 mutant samples to have more peaks. The majority of peaks are positively correlated with survival and positively correlated with gene expression. Constructing a model of the top six atac-seq peaks created a highly accurate survival prediction model (r2 = 0.68). Four of these peaks were still significant after controlling for age, grade, pathology, IDH1 status and gender. Grade II, III, and IV (primary) samples have similar transcription factors and gene modules. However, grade IV (recurrent) samples have strikingly few peaks. Patient-derived glioma cultures showed decreased peak counts following radiation indicating that this may be radiation-induced. This study supports the notion that IDH1 mutant and IDH1 wildtype gliomas have different epigenetic landscapes and that accessible chromatin sites mapped by atac-seq peaks tend to be positively correlated with expression. The data in this study leads to a new model of treatment response wherein glioma cells respond to radiation therapy by closing open regions of DNA.
This dataset
Download · which file do I need?
Direct links to NCBI and ENA, 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.
2 · Re-analyse it
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE295378_RAW.tar (it can run to tens of gigabytes).
3 · Start from the raw reads
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.
Also filed as BioProject PRJNA1254484 and SRA study SRP580688. Searching any of these in the dataset finder brings you back here.
Study design
38 samples, each with a distinct title — no replicated groups
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 38 sample titles: 38 distinct titles with little repetition. 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
- GSM8946884 ATAC-seq of glioma sample MG1 (Glioblastoma, Grade IV, Recurrent, IDH1 WT)
- GSM8946885 ATAC-seq of glioma sample MG2 (Glioblastoma, Grade IV, Recurrent, IDH1 WT)
- GSM8946886 ATAC-seq of glioma sample MG3 (Glioblastoma, Grade IV, Primary, IDH1 WT)
- GSM8946887 ATAC-seq of glioma sample MG4 (Anaplastic astrocytoma, Grade III, Primary, IDH1 WT)
- GSM8946888 ATAC-seq of glioma sample MG5 (Glioblastoma, Grade IV, Primary, IDH1 WT)
- GSM8946889 ATAC-seq of glioma sample MG6 (Glioblastoma, Grade IV, Recurrent, IDH1 WT)
- GSM8946890 ATAC-seq of glioma sample MG7 (Oligodendroglioma, Grade II, Primary, IDH1 Mut)
- GSM8946891 ATAC-seq of glioma sample MG8 (Glioblastoma, Grade IV, Primary, IDH1 WT)
- GSM8946892 ATAC-seq of glioma sample MG9 (Anaplastic oligodendroglioma, Grade III, Primary, IDH1 Mut)
- GSM8946893 ATAC-seq of glioma sample MG10 (Oligodendroglioma, Grade II, Primary, IDH1 Mut)
- GSM8946894 ATAC-seq of glioma sample MG11 (Anaplastic oligodendroglioma, Grade III, Primary, IDH1 Mut)
- GSM8946895 ATAC-seq of glioma sample MG12 (Glioblastoma, Grade IV, Recurrent, IDH1 WT)
- GSM8946896 ATAC-seq of glioma sample MG13 (Anaplastic oligodendroglioma, Grade III, Primary, IDH1 Mut)
- GSM8946897 ATAC-seq of glioma sample MG14 (Anaplastic oligodendroglioma, Grade III, Primary, IDH1 Mut)
- GSM8946898 ATAC-seq of glioma sample MG15 (Glioblastoma, Grade IV, Primary, IDH1 WT)
- GSM8946899 ATAC-seq of glioma sample MG16 (Oligodendroglioma, Grade II, Primary, IDH1 Mut)
- GSM8946900 ATAC-seq of glioma sample MG17 (Oligodendroglioma, Grade II, Primary, IDH1 Mut)
- GSM8946901 ATAC-seq of glioma sample MG18 (Anaplastic astrocytoma, Grade III, Primary, IDH1 Unknown)
- GSM8946902 ATAC-seq of glioma sample MG19 (Glioblastoma, Grade IV, Recurrent, IDH1 Unknown)
- GSM8946903 ATAC-seq of glioma sample MG20 (Glioblastoma, Grade IV, Primary, IDH1 Mut)
- GSM8946904 ATAC-seq of glioma sample MG21 (Glioblastoma, Grade IV, Recurrent, IDH1 Mut)
- GSM8946905 ATAC-seq of glioma sample MG22 (Glioblastoma, Grade IV, Primary, IDH1 WT)
- GSM8946906 ATAC-seq of glioma sample MG23 (Glioblastoma, Grade IV, Recurrent, IDH1 Unknown)
- GSM8946907 ATAC-seq of glioma sample MG24 (Anaplastic oligodendroglioma, Grade III, Primary, IDH1 Mut)
- GSM8946908 ATAC-seq of glioma sample MG25 (Astrocytoma, Grade II, Primary, IDH1 Mut)
- GSM8946909 ATAC-seq of glioma sample MG26 (Anaplastic astrocytoma, Grade III, Primary, IDH1 Mut)
- GSM8946910 ATAC-seq of glioma sample MG27 (Glioblastoma, Grade IV, Primary, IDH1 WT)
- GSM8946911 ATAC-seq of glioma sample MG28 (Glioblastoma, Grade IV, Recurrent, IDH1 WT)
- GSM8946912 ATAC-seq of glioma sample MG29 (Glioblastoma, Grade IV, Recurrent, IDH1 Unknown)
- GSM8946913 ATAC-seq of glioma sample MG30 (Glioblastoma, Grade IV, Recurrent, IDH1 WT)
- GSM8946914 ATAC-seq of glioma sample MG31 (Oligodendroglioma, Grade II, Primary, IDH1 Mut)
- GSM8946915 ATAC-seq of glioma sample MG32 (Astrocytoma, Grade II, Primary, IDH1 Mut)
- GSM8946916 ATAC-seq of glioma sample MG33 (Glioblastoma, Grade IV, Primary, IDH1 WT)
- GSM8946917 ATAC-seq of glioma sample MG34 (Glioblastoma, Grade IV, Recurrent, IDH1 WT)
- GSM8946918 ATAC-seq of glioma sample MG35 (Glioblastoma, Grade IV, Recurrent, IDH1 Mut)
- GSM8946919 ATAC-seq of glioma sample MG36 (Glioblastoma, Grade IV, Primary, IDH1 WT)
- GSM8946920 ATAC-seq of glioma sample MG37 (Glioblastoma, Grade IV, Recurrent, IDH1 Mut)
- GSM8946921 ATAC-seq of glioma sample MG38 (Anaplastic oligodendroglioma, Grade III, Primary, IDH1 WT)
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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.