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Inhibiting the RNA helicase DDX3X in Burkitt lymphoma induces oxydative stress and impedes tumor progression in xenografts

GSE294862 Homo sapiens (human) RNA-seq (gene expression) 30 samples Submitted 2025/08/13 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 30 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
Burkitt lymphomaThis series is part of our curated briefing on it.
Samples
30 samples: 12 conditions, mostly in duplicateGroups 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
Inhibiting the RNA helicase DDX3X in Burkitt lymphoma induces oxydative stress and impedes tumor progression in xenograftsFrontiers in cell and developmental biology · 2025
Summary (written by the submitters)
Burkitt Lymphoma (BL), an aggressive B-cell lymphoma driven by MYC translocations, requires intensive chemotherapy treatments which deliver high effectiveness yet increase future risks of developing secondary malignancies. We have previously shown that DDX3X, an RNA helicase frequently mutated in BL, is essential for B cell lymphomagenesis in mice.
Read the full summary ↓
To assess if DDX3X could therefore represent a promising therapeutic target, we tested two DDX3X inhibitors, the well characterized RK-33 and the more potent newly developed C1, in three BL cell lines (CA46, Raji, Daudi). We found that the three cell lines exhibited differential sensitivities to the drugs in vitro, with Daudi being the most susceptible and Raji the most resistant. In vivo, RK-33 treatment in a xenograft BL model reduced tumor progression in all cell lines, with the Daudi cells being the most responsive to the treatment, albeit with variable efficacy compared to the clinical drug Pevonedistat. Transcriptomic and proteomic analyses indicated that RK-33-mediated inhibition of DDX3X and DDX3X ablation through siRNA affects oxidative phosphorylation among other pathways and leads to an increase of intracellular reactive oxygen species (ROS). A CRISPR chemogenomic screen to identify synthetic lethalities linked to RK-33 implicated enzymes of the glutathione synthesis pathway. We therefore tested the inhibition of the glutathione pathway with buthionine sulfoximine and showed that it reduced the CC50 of RK-33 in BL cells lines. Our findings not only support DDX3X as a therapeutic target in BL, but also provide evidence for a combinatorial strategy to improve the efficacy of current treatments.
Published in
Inhibiting the RNA helicase DDX3X in Burkitt lymphoma induces oxydative stress and impedes tumor progression in xenografts
Beauchemin H, Dalloul Z, Piskor EM et al. · Frontiers in cell and developmental biology 2025 · PMID 40772229 · doi:10.3389/fcell.2025.1642006
This dataset
Open GSE294862 in finder → Find more human RNA-seq datasets → Burkitt lymphoma 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 GSE294862_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 PRJNA1251870 and SRA study SRP579337. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40772229) ↗
Study design
12 conditions, mostly in duplicate
ca46_dmso ×2 ca46_rk33 ×2 ca46_scrbl ×2 ca46_siddx3xy ×2 ca46_siddx3x ×2 ca46_siddx3y ×2 raji_dmso ×2 raji_rk33 ×2 +10 more

Supports a between-group comparison across 24 samples.

How we read this: 12 replicated groups read from 30 sample titles; they account for 24 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 Burkitt lymphoma datasets

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