← BioTransfer GEO Dataset Finder
GEO series

Combination of epigenetic enzyme inhibitors, GSKJ4 and Belinostat, reveals efficacy in IDH1 mutant gliomas

GSE134120 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2024/07/14 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 16 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Topic
Lower-grade gliomaThis series is part of our curated briefing on it.
Samples
16 samples: 8 conditions, mostly in duplicateGroups 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)
Mutations in IDH1 and IDH2 genes are very common in low grade gliomas and secondary GBM. They induce hypermethylation of DNA and histones in tumor cells, and generate a specific epigenetic phenotype. Therefore, we decided to perform a chemical screen consisting of inhibitors of epigenetic regulators on patient-derived IDH mutant cell lines.
Read the full summary ↓
Dual combinations of hit inhibitors in low doses were also analyzed to increase treatment efficiency. Individual and combinatorial effects of these inhibitors were also analyzed in wild type and IDH mutant pair of A172 GBM cell line that was derived by ectopic overexpression of mutant IDH1. GSK-J4 and Belinostat combination was highly effective on both patient-derived and engineered IDH mutant cells compared to wild type cells. Interestingly, sensitized IDH mutant cells were recovered via mutant IDH inhibitor, GSK864, which is thought as a candidate drug for IDH mutant glioma. On the other hand, viability of non-malignant fibroblasts were not affected from these drugs in these doses. GSK-J4 and Belinostat combination induce apoptosis which was shown by increased Caspase 3/7 activity, PARP cleavage and recovery with general caspase inhibitor (Z-VAD-FMK). Change in histone modifications such as H3K4me3, H3K9me3, H3K27me3 and H3K27ac were observed after mutant IDH overexpression and also drug treatments. RNA-seq and GSEA analysis revealed activation of unfolded protein and viral response pathways in IDH mutant cells which indicate increased cell stress. GSKJ4 and Belinostat induces cell cycle arrest and apoptosis by further increasing cell stress probably because of dramatic changes in chromatin structure.
This dataset
Open GSE134120 in finder → Find more human RNA-seq datasets → Lower-grade glioma landscape →
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.

Series matrix ↓
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 GSE134120_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA553818 and SRA study SRP214156. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in duplicate
A172 IDH MUT-GSK864 ×2 A172 WT ×2 A172 WT-GSK864 ×2 A172 IDH MUT ×2 MGG152-Ctrl ×2 MGG152-GSKJ4 ×2 MGG152-Bel ×2 MGG152-GSKJ4+Bel ×2

Supports a between-group comparison across 16 samples.

How we read this: 8 replicated groups read from 16 sample titles; they account for 16 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
More Lower-grade glioma datasets

Search all human RNA-seq 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.