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Discovery and characterisation of VPRBP/DCAF1 kinase inhibitor analogues as microtubular destabilising agents with potent anti-myeloma activity

GSE295791 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/10/06 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 6 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
Discovery and Characterization of VPRBP/DCAF1 Kinase Inhibitor Analogs as Microtubular Destabilizing Agents with Potent Antimyeloma ActivityMolecular cancer therapeutics · 2026
Summary (written by the submitters)
Multiple myeloma is a plasma cell malignancy that is susceptible to drugs targeting protein homeostasis such as thalidomide analogues and proteasome inhibitors. Thalidomide analogues modulate the activity of DDB1/CUL4 E3-ligase complexes to perturb substrate recognition and proteasomal degradation thereof. We hypothesised that the cellular pool of DDB1/CUL4 associated factors (DCAFs) may mediate other essential plasma cell processes and offer new targets for therapeutic intervention.
Read the full summary ↓
Unbiased genetic screening identified DCAF1 (also known as Vpr-binding protein; VPRBP) as essential for myeloma cell survival with a multidomain structure offering several distinct opportunities for drug development. Utilising B32B3, a previously disclosed DCAF1 kinase inhibitor as a template, we developed a series of analogues with enhanced anti-myeloma potency. As anti-myeloma activity did not associate with dephosphorylation of known DCAF1 kinase substrates, we correlated drug-induced cellular phenotypes with whole-genome CRISPR/Cas9 resistance screening to further define mechanistic activity. These studies identified B32B3 analogues as microtubular destabilising agents with potential DCAF1 kinase independent properties and in vivo efficacy in multiple myeloma and lymphoma.
Published in
Discovery and Characterization of VPRBP/DCAF1 Kinase Inhibitor Analogs as Microtubular Destabilizing Agents with Potent Antimyeloma Activity
Susanto O, Gruber E, Wun CM et al. · Molecular cancer therapeutics 2026 · PMID 41185616 · doi:10.1158/1535-7163.MCT-25-0306
This dataset
Open GSE295791 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 GSE295791_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 PRJNA1256382 and SRA study SRP581767. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41185616) ↗
Study design
6 conditions, mostly in triplicate
B2B3-24h ×3 B2B3-6h ×3 DMSO-24h ×3 VPR8-24h ×3 VPR8-6h ×3 DMSO-6h ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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 Multiple myeloma datasets

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