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IRF2 is an Essential Transcription Factor with Pathogenic and Prognostic Impact in Multiple Myeloma

GSE302052 Homo sapiens (human) RNA-seq (gene expression) 257 samples Submitted 2026/07/29 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 257 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
Multiple myelomaThis series is part of our curated briefing on it.
Samples
257 samples: 21 conditions, mostly in triplicateGroups 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.
Paper
IRF2 is an essential transcription factor with pathogenic and prognostic impact in multiple myelomaBlood · 2026
Summary (written by the submitters)
Multiple Myeloma (MM), the second most prevalent hematologic malignancy, remains incurable, highlighting the need to identify molecular drivers of disease progression and new therapies. Using a CRISPR-Cas9 library screening approach in MM cells, we identified 22 essential transcription factors (TFs), including members of the interferon regulatory factor (IRF) family.
Read the full summary ↓
Remarkably, in addition to the well-known IRF4, IRF2 emerged as a critical TF in MM. Cut&Run experiments demonstrated that IRF2 binds extensively to chromatin, both independently and in cooperation with IRF1 and IRF4. While IRF2-unique regions were predominantly associated with active promoters, regions bound by IRF2/1/4 were biased towards introns. Functionally, IRF2 contributes to MM cell survival by suppressing necroptosis and promoting cell migration. Notably, IRF2-dependent transcriptional dysregulation was evident in precursor conditions such as MGUS and SMM, suggesting a role in early disease evolution. In addition to its role as early factor, IRF2 levels also seem to influence disease progression, as MMs with higher expression showed worse progression-free survival (PFS) and overall survival (OS) in both univariate and multivariate analyses, even after adjusting for common MM genetic risk factors. In conclusion, IRF2 constitutes an underappreciated essential TF involved in the pathogenesis and clinical behavior of MM. Its inhibition leads to dysregulation of key signaling pathways in MM pathogenesis, highlighting its potential as a therapeutic target.
Published in
IRF2 is an essential transcription factor with pathogenic and prognostic impact in multiple myeloma
Gómez-Echarte N, Carrasco-León A, Maiqués-Díaz A et al. · Blood 2026 · PMID 42247308 · doi:10.1182/blood.2025029422
This dataset
Open GSE302052 in finder → Find more human RNA-seq datasets → Multiple myeloma 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 GSE302052_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 PRJNA1288428 and SRA study SRP599192. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42247308) ↗
Study design
21 conditions, mostly in triplicate
MM ×150 SMM ×33 MGUS ×19 HD ×10 KMS-11 Scr ×3 MM.1R Scr ×3 KMS28-G1 ×3 KMS28-Scr ×3 +15 more

Supports a between-group comparison across 255 samples.

How we read this: 21 replicated groups read from 257 sample titles; they account for 255 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

+ 217 more — browse all 257 samples with per-sample file links →

More Multiple myeloma datasets

Search all human RNA-seq datasets in GEO →

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