GEO series

Harnessing the E3 ligase SPOP for targeted degradation of the NUP98::KDM5A fusion oncoprotein

GSE297415 Mus musculus (mouse) RNA-seq (gene expression) 17 samples Submitted 2025/11/21 Platform GPL30173Platform GPL34290

At a glance

RNA-seq (gene expression) · mouse · 17 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: Mus musculus (mouse)
Topic: Acute myeloid leukemiaThis series is part of our curated briefing on it.
Samples: 17 samples: 11 distinct titles, 2 of them repeatedGroups 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: Harnessing the E3 ligase SPOP for targeted degradation of the NUP98::KDM5A fusion oncoproteinCell reports · 2025

Summary (written by the submitters)

NUP98-rearranged (NUP98-r) acute myeloid leukemia (AML) is associated with poor clinical outcomes and represents a major therapeutic challenge due to the lack of strategies for the direct elimination of NUP98-fusion oncoproteins. While targeted degradation of cancer-driving oncoproteins is an attractive strategy, the molecular mechanisms controlling NUP98 fusion oncoprotein stability are not known.

Read the full summary ↓

Here, we used CRISPR/Cas9 screening to identify the E3 ligase SPOP as a direct regulator of NUP98 oncofusion stability and a novel tumor suppressor in NUP98-r AML. SPOP loss caused a selective increase of NUP98 fusion oncoprotein levels, and promoted leukemia cell proliferation. Leveraging this specificity, we show that induced proximity of SPOP and the NUP98::KDM5A fusion oncoprotein via a bioPROTAC approach induced full clearance of the fusion oncoprotein, and drove terminal differentiation and apoptosis of NUP98-r leukemia cells in vitro and in vivo. Altogether, our study identifies the SPOP E3 ligase as a direct regulator of NUP98 oncofusion stability and presents a blueprint for redirecting the ubiquitin proteasome system to selectively target cancer driving fusion oncoproteins.

Published in

Harnessing the E3 ligase SPOP for targeted degradation of the NUP98::KDM5A fusion oncoprotein

Kirkiz E, Kaufmann G, Bergqvist S et al. · Cell reports 2025 · PMID 41307993 · doi:10.1016/j.celrep.2025.116602

This dataset

Open GSE297415 in finder → Find more RNA-seq datasets → Acute myeloid leukemia 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 GSE297415_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 PRJNA1263808 and SRA study SRP585889. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41307993) ↗

Study design

11 distinct titles, 2 of them repeated

HEK_WT_A1061 ×4 HEK_c3_5 ×4

How we read this: Read from 17 sample titles: 11 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

GSM8990848 HEK_WT_A1061_1
GSM8990849 HEK_WT_A1061_2
GSM8990850 HEK_WT_A1061_3
GSM8990851 HEK_WT_A1061_4
GSM8990852 HEK_c3_5_1
GSM8990853 HEK_c3_5_2
GSM8990854 HEK_c3_5_3
GSM8990855 HEK_c3_5_4
GSM8990856 EV_1_1
GSM8990857 EV_2_1
GSM8990858 EV_3_1
GSM8990859 SPOP_d3_1_1
GSM8990860 SPOP_d3_2_1
GSM8990861 SPOP_d3_3_1
GSM8990862 SPOP_d6_1_1
GSM8990863 SPOP_d6_2_1
GSM8990864 SPOP_d6_3_1

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