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Dual degradation of IKK1 and NR4A1 for AML therapy

GSE324608 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2026/07/27 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 36 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
Acute myeloid leukemiaThis series is part of our curated briefing on it.
Samples
36 samples: 12 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.
Summary (written by the submitters)
Acute myeloid leukemia (AML) is an aggressive hematologic malignancy with poor clinical outcomes and limited therapeutic options. Aberrant activation of the IKKβ–NF-κB pathway occurs in approximately 40% of AML cases and contributes to leukemogenesis. However, pharmacological inhibition of IKKβ has been limited by serious toxicities, including neutrophilia.
Read the full summary ↓
Here we identify IKKβ and NR4A1 as cooperative drivers of AML progression and develop a proteolysis-targeting chimera (PROTAC) to simultaneously degrade both proteins. Although NR4A1 has previously been described as a tumor suppressor in AML, our findings demonstrate that NR4A1 exhibits context-dependent oncogenic functions in AML. Notably, IKKβ and NR4A1 are highly expressed in AML associated with poor clinical outcomes and mutually enhance each other’s expression, playing synergistic roles to promote AML pathogenesis. To therapeutically target this pathway, we designed and synthesized a series of celastrol-based PROTACs that exploit celastrol’s ability to bind both IKKβ and NR4A1. Among these compounds, the lead A9 induced potent cytotoxicity in multiple AML cell lines and primary AML samples through CRBN E3 ligase–dependent dual degradation of IKKβ and NR4A1. In vivo, A9 suppressed leukemia progression in a KMT2A::MLLT3 AML mouse model without inducing neutrophilia, supporting dual PROTAC-mediated degradation as a promising therapeutic strategy.
This dataset
Open GSE324608 in finder → Find more human 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 GSE324608_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 PRJNA1436009 and SRA study SRP683008. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 conditions, mostly in triplicate
MOLM-13 DMSO 72 h_1 ×3 MOLM-13 DMSO 72 h_2 ×3 MOLM-13 DMSO 72 h_3 ×3 MOLM-13 A9 72 h_1 ×3 MOLM-13 A9 72 h_2 ×3 MOLM-13 A9 72 h_3 ×3 MONO-MAC-6 DMSO 72 h_1 ×3 MONO-MAC-6 DMSO 72 h_2 ×3 +4 more

Supports a between-group comparison across 36 samples.

How we read this: 12 replicated groups read from 36 sample titles; they account for 36 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 Acute myeloid leukemia datasets

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