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Genome-wide CRISPR Screen Identifies DNTT as a Key Regulator of Inotuzumab Ozogamicin Response in B-cell Acute Lymphoblastic Leukemia

GSE264338 Homo sapiens (human) RNA-seq (gene expression) 34 samples Submitted 2024/12/31 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 34 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 lymphoblastic leukemiaThis series is part of our curated briefing on it.
Samples
34 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.
Paper
DNTT-mediated DNA damage response drives inotuzumab ozogamicin resistance in B-cell acute lymphoblastic leukemiaBlood · 2025
Summary (written by the submitters)
Inotuzumab Ozogamicin (InO) is an antibody-drug conjugate with striking efficacy in B-cell acute lymphoblastic leukemia (B-ALL). However, there is wide inter-patient variability in treatment response, and the genetic basis of this variation remains largely unknown. Using a genome-wide CRISPR screen, we discovered the loss of DNTT as a top driver of InO resistance.
Read the full summary ↓
Our results directly show the effects of DNTT expression on H2AX phosphorylation, DNA damage response signaling, cell cycle arrest and mitochondrial apoptotic priming, ultimately conferring leukemia resistance to InO. Screening 196 primary human B-ALL samples for InO sensitivity confirmed the impact of DNTT expression on InO response. Additionally, low DNTT expression was found in the residual leukemia blasts post InO treatment in patients enrolled in the COG trial AALL1621. Collectively, we demonstrate that loss of DNTT diminishes B-ALL sensitivity to InO in vitro and promotes leukemia cell survival during InO treatment in vivo.
Published in
DNTT-mediated DNA damage response drives inotuzumab ozogamicin resistance in B-cell acute lymphoblastic leukemia
Escherich CS, Moriyama T, Li Z et al. · Blood 2025 · PMID 39791601 · doi:10.1182/blood.2024026085
This dataset
Open GSE264338 in finder → Find more human RNA-seq datasets → Acute lymphoblastic 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 GSE264338_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 PRJNA1101988 and SRA study SRP502632. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39791601) ↗
Study design
12 conditions, mostly in triplicate
Nalm6_WT_Contr ×3 Nalm6_KO_Contr ×3 Nalm6_WT_InO ×3 Nalm6_KO_InO ×3 RS411_WT_Contr ×3 RS411_KO_Contr ×3 RS411_WT_InO ×3 REH_WT_InO ×3 +4 more

Supports a between-group comparison across 34 samples.

How we read this: 12 replicated groups read from 34 sample titles; they account for 34 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 lymphoblastic leukemia datasets

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