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Nuclear respiratory factor 1(NRF1) sustains the development, progression and resistance of Multiple Myeloma [RNA-Seq]

GSE285195 Homo sapiens (human) Single-cell RNA-seq 21 samples Submitted 2025/09/09 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 21 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
21 samples: 12 × RNA_seq_Multiple_Myeloma_MM vs 9 × RNA_seq_MGUS_CBGroups 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
Nuclear respiratory factor 1 promotes cell survival in multiple myeloma under proteasome inhibition therapyBlood · 2025
Summary (written by the submitters)
Multiple myeloma (MM) is a hematological malignancy characterized by the clonal proliferation of plasma cells within the bone marrow. Despite significant advancements in understanding the pathogenesis and the development of novel therapeutic approaches, MM remains incurable. Emerging evidence indicates aberrant epigenetic activity at cis-regulatory elements (CREs).
Read the full summary ↓
However, the characterization of these events and the definition of relative impact with MM phenotype is only partially known. To address this gap, we comprehensively analyzed the epigenetic changes occurring during MM progression to identify the events and the key transcriptional regulators sustaining the disease.We profiled a cohort of 55 patient MM samples at diagnosis, post-therapy, and relapse and a cohort of 16 MGUS samples using ATAC-seq. Then, we used footprinting analysis to identify detailed changes in transcription factor engagement. We conducted experiments using in vitro and in vivo methods, including primary cell line models and a MM mouse model (vk-Myc). We employed high-throughput techniques such as ChIP-seq, RNA-seq, and RNA-Single Cell. Our results were confirmed using shRNA interference, dCas9-KRAB-Mediated interference, and the usage of an independent cohort.We stratified the pervasiveness of open chromatin loci in our MM cohort. Penetrant loci were enriched for the binding of the Nuclear Respiratory Factor 1 (NRF1) in MM but not in MGUS samples. These findings were validated using 144 published ATAC-seq profiles of MM. ChIP-seq analysis on 15 MM and 6 MGUS patients confirmed that NRF1 sustains the activity of promoters and enhancers exclusively in MM but not in MGUS. A distinctive NRF1-dependent transcriptional signature of 103 genes was identified, correlating with aggressive disease and bad prognosis (CoMMpass dataset). This signature defines a group of 195 patients with a significantly poorer prognosis (20 months overall survival gap). The gene signature is enriched for survival pathways and ubiquitination. Our experiments show that NRF1 drives the proteasome homeostatic mechanism by enhancing phosphorylation and ubiquitination. NRF1 levels increase during therapy with proteasome inhibitors in our models. We identified a strong MM-specific enhancer element producing eRNA, looping towards the NRF1 gene. Interference with this eRNA downregulated NRF1 expression. Lowering eRNA in the presence of bortezomib increased cell proliferation loss, suggesting potential clinical applications for eRNA interference as an adjuvant to proteasome inhibitors.Collectively, our research supports that MM cells exhibit an addiction to NRF1, providing a survival advantage and therapy escape mechanisms. NRF1 binding reflects higher proteotoxic stress in malignant plasma cells and is crucial for their adaptability. Interfering with NRF1 and its regulatory elements significantly impairs MM therapy escape potential, highlighting its therapeutic benefit in MM treatment strategies.
Published in
Nuclear respiratory factor 1 promotes cell survival in multiple myeloma under proteasome inhibition therapy
Bruno T, Cappelletto MC, Cortile C et al. · Blood 2025 · PMID 40920573 · doi:10.1182/blood.2025028441
This dataset
Open GSE285195 in finder → Find more human RNA-seq datasets →
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 GSE285195_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1201777 and SRA study SRP553247. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40920573) ↗
Study design
12 × RNA_seq_Multiple_Myeloma_MM vs 9 × RNA_seq_MGUS_CB

Supports a between-group comparison across 21 samples.

How we read this: 2 replicated groups read from 21 sample titles; they account for 21 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
Datasets on a similar topic

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