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Combined Targeting of de novo Pyrimidine Synthesis and ATR Promotes ATF4-Mediated Cell Death in TP53-Deficient ALL

GSE308646 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2026/07/29 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 24 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)
Samples
24 samples: 8 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
Combined inhibition of de novo pyrimidine synthesis and ATR promotes ATF4-mediated cell death in TP53-deficient ALLHemaSphere · 2026
Summary (written by the submitters)
Mutations or deletions affecting the TP53 gene predict a dismal outcome in relapsed acute lymphoblastic leukemia (ALL), with limited curative treatment options available. Due to their highly proliferative state, ALL cells are strongly dependent on nucleotide synthesis. Inhibitors of dihydroorotate dehydrogenase (DHODH), a pivotal enzyme in de novo pyrimidine biosynthesis, have demonstrated promising single-agent efficacy in some ALL and acute myeloid leukemia (AML) preclinical models.
Read the full summary ↓
Using both isogenic TP53 cell line models and patient-derived xenografts (PDX), we show that dual inhibition of DHODH and Ataxia telangiectasia and Rad3 related (ATR) produces pronounced anti-leukemic effects, irrespective of the TP53 status. Through integrated transcriptomic and metabolomic analyses, we show that combined inhibition of DHODH and ATR leads to a reduced flux of glucose to the TCA cycle, accompanied by an increase in oxidative stress. This metabolic phenotype triggers cell death through a mechanism converging on Activating Transcription Factor 4 (ATF4), a key integrator of cellular responses to metabolic and oxidative stress, which operates largely independent of p53. Taken together, our findings identify ATF4-mediated cell death as a previously unrecognized vulnerability in TP53-deficient ALL.
Published in
Combined inhibition of de novo pyrimidine synthesis and ATR promotes ATF4-mediated cell death in TP53-deficient ALL
Grünewald KJT, Kes MMG, Stoll GR et al. · HemaSphere 2026 · PMID 42519367 · doi:10.1002/hem3.70439
This dataset
Open GSE308646 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 GSE308646_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 PRJNA1331786 and SRA study SRP622563. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42519367) ↗
Study design
8 conditions, mostly in triplicate
RCH-ACV TP53 KO Orludodstat Single treatment ×3 RCH-ACV TP53 KO Berzosertib Single treatment ×3 RCH-ACV TP53 KO Combination treatment ×3 RCH-ACV TP53 KO Untreated ×3 RCH-ACV TP53 WT Orludodstat Single treatment ×3 RCH-ACV TP53 WT Berzosertib Single treatment ×3 RCH-ACV TP53 WT Combination treatment ×3 RCH-ACV TP53 WT Untreated ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 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
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