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Differential RNA splicing analysis with or without IL-6 in multiple myeloma cells

GSE298694 Homo sapiens (human) RNA-seq (gene expression) 42 samples Submitted 2026/02/15 Platform GPL24676Platform GPL28038
At a glance

RNA-seq (gene expression) · human · 42 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
42 samples: 42 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.
Paper
IL-6-driven POU2AF1 and ELL2 are key regulators of multiple myeloma-distinct transcriptional and splicing programsBlood advances · 2026
Summary (written by the submitters)
Multiple myeloma (MM) is a plasma cell neoplasm that depends on the bone marrow (BM) microenvironment; however, the underlying mechanisms of epigenetic contribution to the pathogenesis of MM are incompletely understood. Here, we delineate the epigenetic-driven transcriptional and splicing program crucial for MM.
Read the full summary ↓
We recharacterized transcriptional program induced by IL-6/JAK/STAT3 pathway by ChIP-seq and RNA-seq analyses combined with CRIPSR knockout screening database, and identified B cell lineage factors, POU2AF1 and ELL2, as crucial IL-6/JAK/STAT3 targets that are essential for MM cell growth and survival. Genetic depletion of these factors suppressed MM cell growth in vitro and in the xenograft model of IL-6 humanized mice. Mechanistically, POU2AF1 and ELL2 govern MM-distinct transcriptional program representing immaturity, and IL-6/JAK/STAT3 pathway augments this program through upregulating and recruiting these factors to the MM-signature genes. Furthermore, we showed that IL-6 induces alternative splicing that is partly mediated by POU2AF1. Proteomic study identified novel POU2AF1-associated factors that converge in regulation of RNA, including RNA splicing. Indeed, POU2AF1 is adjacent to multiple splicing factors required for MM cell survival and is involved in the organization of nuclear speckles. Finally, we showed that gapmer antisense oligonucleotides (ASOs) targeting POU2AF1 inhibit its expression and MM cell growth in the presence of soluble BM stromal cell factors, including IL-6. Our data demonstrate that IL-6-driven B cell-lineage factors are the vulnerability of MM cells and may represent novel therapeutic targets for this incurable tumor.
Published in
IL-6-driven POU2AF1 and ELL2 are key regulators of multiple myeloma-distinct transcriptional and splicing programs
Ohguchi Y, Ajiro M, Ogiya D et al. · Blood advances 2026 · PMID 41925579 · doi:10.1182/bloodadvances.2025018710
This dataset
Open GSE298694 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 GSE298694_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 PRJNA1270959 and SRA study SRP589469. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41925579) ↗
Study design
42 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 42 sample titles: 42 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

+ 2 more — browse all 42 samples with per-sample file links →

More Multiple myeloma 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.