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IRF2BP2-mediated MHC-I expression controls cytotoxic T cell responses in acute myeloid leukemia [RNA-Seq]

GSE250160 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/12/14 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 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
Acute myeloid leukemiaThis series is part of our curated briefing on it.
Samples
12 samples: 6 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)
Immunotherapy, including immune checkpoint blockade (ICB), has become an effective option for treating patients with cancer, especially those with solid tumors. Recently, T cell-based cellular therapies have extended the scope of immunotherapy to B-cell malignancies. Immunotherapy options for patients with acute myeloid leukemia (AML), however, are limited.
Read the full summary ↓
To identify new immunotherapy approaches for AML, we performed CRISPR/Cas9 AML T cell co-culture screens. We determined that depletion of the transcription factor IRF2BP2 leads to enhanced T cell killing both in vitro and in vivo. Gene expression profiling and flow cytometry studies confirmed enhanced MHC-I expression upon IRF2BP2 loss. Chromatin binding analysis further revealed a regulatory axis whereby MHC-I expression is repressed by IRF2BP2 through its repression of the interferon alpha pathway. Our studies have identified the inhibition of IRF2BP2 as a potential strategy for enhancing T-cell-based therapies in patients with AML
This dataset
Open GSE250160 in finder → Find more human RNA-seq datasets → Acute myeloid leukemia 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 GSE250160_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 PRJNA1052127 and SRA study SRP477870. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly in duplicate
MOLM13, sgIRF2BP2#1, ×2 MOLM13, sgIRF2BP2#2, ×2 MOLM13, sgNT, ×2 THP1, sgIRF2BP2#1, ×2 THP1, sgIRF2BP2#2, ×2 THP1, sgNT, ×2

Supports a between-group comparison across 12 samples.

How we read this: 6 replicated groups read from 12 sample titles; they account for 12 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 Acute myeloid leukemia datasets

Search all human RNA-seq datasets in GEO →

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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.