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Combining anti-PD1 and vorinostat improves anti-tumor treatment in IDH-mutant brain tumors

GSE248513 Mus musculus (mouse) RNA-seq (gene expression) 15 samples Submitted 2024/05/01 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 15 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
Mus musculus (mouse)
Samples
15 samples
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)
Enhancer RNA (eRNA) is critical element with highly specific pattern in regulatory network across infiltrated immune cells. Herein we developed eRNA immunotherapy signature (eRIS) based on these eRNAs which significantly connected with anti-tumor immune cells. The eRIS was highly correlated with objective response rate (ORR) to immune checkpoint blockade (ICB) treatment, and was significantly increased in these patients who benefit from ICB treatment.
Read the full summary ↓
By integrating with pharmacogenomics datasets, we screened hundreds of eRIS associated anti-cancer drugs, which showed potential in improving immunotherapy with cancer type or subtype-specific specific manner. We further characterized one drug, the HDAC inhibitor vorinostat, in isocitrate dehydrogenase mutant gliomas, and found Combining vorinostat with anti-PD-1 could decrease tumor size and increase survival time in vivo by enhancing abundance of anti-tumor immune cells. We further provided eRIS markers which showed strong capacity of eRIS in predicting immunotherapy response in clinical samples or animal models. Our study revealed the potential utility of eRIS to improve immunotherapy response by identifying combinational drugs, that provide novel insights to benefit patients in certain cancer or subtypes.
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 GSE248513_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: 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 PRJNA1044403 and SRA study SRP473862. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 15 more — browse all 15 samples with per-sample file links →

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