GEO series

IRF4 requires ARID1A to establish plasma cell identity in multiple myeloma (ATAC-Seq human 16)

GSE253703 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 16 samples Submitted 2024/05/01 Platform GPL30173

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 16 samples

What it is: ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism: Homo sapiens (human)
Topic: Multiple myelomaThis series is part of our curated briefing on it.
Samples: 16 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)

Multiple myeloma (MM) is an incurable malignancy of plasma cells that exploits transcriptional networks underpinning normal plasma cell biology to drive malignant growth and survival. The transcription factor IRF4 serves as the principal architect of plasma cell identity, and MM cells are addicted to IRF4 expression for their survival.

Read the full summary ↓

To discover unique molecular vulnerabilities in MM, we employ a multi-omics approach integrating functional genomics screening, spatial-proteomics, and global chromatin mapping. We find that ARID1A, a member of the SWI/SNF chromatin remodeling complex, is both required for IRF4 expression and functionally associated with IRF4 protein on chromatin. Conditional deletion of Arid1a in activated murine B cells thwarts subsequent plasma cell differentiation by disrupting IRF4-dependent transcriptional networks, thus defining ARID1A as a novel plasma cell vulnerability. Targeting ARID1A-dependent SWI/SNF activity via SMARCA2/4 inhibition induces a rapid loss of IRF4-target gene expression and quenches global oncogenic amplification of gene expression driven by MYC, resulting in profound toxicity to MM cells. Notably, SWI/SNF-dependent genes are upregulated in MM patients with aggressive disease, and SMARCA2/4 inhibitors retain their activity in immunomodulatory drug (IMiD)-resistant MM cells. To fully harness the potential of these drugs, we use combinatorial drug screens to uncover profound synergistic toxicity between SMARCA2/4 and MEK inhibitors. Thus, targeting SWI/SNF activity potently represses an IRF4-MYC feed forward loop and provides a feasible path forward to effectively treat this incurable disease.

This dataset

Open GSE253703 in finder → Find more human ChIP / ATAC / CUT&Tag 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 GSE253703_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1066803 and SRA study SRP484831. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 16 more — browse all 16 samples with per-sample file links →

More Multiple myeloma datasets

GSE167969 ATAC-seq and RNA-Seq of Multiple Myeloma 46 samples same disease briefing · shares multiple, atac-seq, myeloma
GSE178328 Genome-wide maps of chromatin state in DEAF1 overexpression (OE in Multiple Myeloma) 2 samples same disease briefing · shares multiple, myeloma
GSE161195 Single cell RNA-seq of relapsed and refractory multiple myeloma patients defines new resistance pathways and targeted treatments 213 samples same disease briefing · shares multiple, myeloma
GSE155631 Oncogenic mechanisms of DIS3 mutations in Multiple Myeloma 62 samples same disease briefing · shares multiple, myeloma
GSE148715 “Direct to Drug” screening as a precision medicine tool in multiple myeloma 38 samples same disease briefing · shares multiple, myeloma
GSE167968 RNA-seq of Multiple Myeloma 33 samples same disease briefing · shares multiple, myeloma
GSE179453 Expression data from control-knockdown (CTR-KD) and MAST4-KD human multiple myeloma (MM) cell lines 6 samples same disease briefing · shares multiple, myeloma
GSE167042 Splicing modulation increases BCL2 dependence and sensitizes Multiple Myeloma cells to Venetoclax 4 samples same disease briefing · shares multiple, myeloma

Search all human ChIP / ATAC / CUT&Tag 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.