GEO series

The XPO7-NPAT axis represents key vulnerabilities in TP53-mutated acute myeloid leukemia (RNA-Seq)

GSE264595 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2026/04/22 Platform GPL21626

At a glance

RNA-seq (gene expression) · mouse · 18 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)
Samples: 18 samples: 6 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)

Mutation of TP53, a tumor suppressor in cancer, is common and leads to extremely poor prognosis. To identify vulnerabilities in TP53-mutated tumors, we performed genome-wide CRISPR/Cas9 screens using isogenic Trp53 wild-type and knockout mouse acute myeloid leukemia (AML) lines. Here, we show that histone gene regulation governed by the XPO7-NPAT pathway is essential for survival of TP53-mutated AML cells.

Read the full summary ↓

In TP53 wild-type cells, XPO7 enhances p53 nuclear localization and functions as a tumor suppressor, but in TP53-mutated cells, XPO7 promotes cell proliferation by retaining NPAT, a histone gene activator, in the nucleus. NPAT depletion led to genome-wide histone loss, enhancing vulnerability to genotoxic stress. Human AML cases show predominant expression of XPO7 and NPAT when TP53 is mutated, suggesting a potential therapeutic vulnerability.

This dataset

Open GSE264595 in finder → Find more mouse 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 GSE264595_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 PRJNA1103208 and SRA study SRP503434. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

6 conditions, mostly in triplicate

Xpo7WT, DMSO, RNA, ×3 Xpo7KO, DMSO, RNA, ×3 Xpo7WT, MDM2i, RNA, ×3 Xpo7KO, MDM2i, RNA, ×3 NpatKI, dTAG, 0hr, RNA, ×3 NpatKI, dTAG, 3hr, RNA, ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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

GSM8223520 Xpo7WT, DMSO, RNA, rep1 Xpo7WT, DMSO, RNA,
GSM8223521 Xpo7WT, DMSO, RNA, rep2 Xpo7WT, DMSO, RNA,
GSM8223522 Xpo7WT, DMSO, RNA, rep3 Xpo7WT, DMSO, RNA,
GSM8223523 Xpo7KO, DMSO, RNA, rep1 Xpo7KO, DMSO, RNA,
GSM8223524 Xpo7KO, DMSO, RNA, rep2 Xpo7KO, DMSO, RNA,
GSM8223525 Xpo7KO, DMSO, RNA, rep3 Xpo7KO, DMSO, RNA,
GSM8223526 Xpo7WT, MDM2i, RNA, rep1 Xpo7WT, MDM2i, RNA,
GSM8223527 Xpo7WT, MDM2i, RNA, rep2 Xpo7WT, MDM2i, RNA,
GSM8223528 Xpo7WT, MDM2i, RNA, rep3 Xpo7WT, MDM2i, RNA,
GSM8223529 Xpo7KO, MDM2i, RNA, rep1 Xpo7KO, MDM2i, RNA,
GSM8223530 Xpo7KO, MDM2i, RNA, rep2 Xpo7KO, MDM2i, RNA,
GSM8223531 Xpo7KO, MDM2i, RNA, rep3 Xpo7KO, MDM2i, RNA,
GSM8223532 NpatKI, dTAG, 0hr, RNA, rep1 NpatKI, dTAG, 0hr, RNA,
GSM8223533 NpatKI, dTAG, 0hr, RNA, rep2 NpatKI, dTAG, 0hr, RNA,
GSM8223534 NpatKI, dTAG, 0hr, RNA, rep3 NpatKI, dTAG, 0hr, RNA,
GSM8223535 NpatKI, dTAG, 3hr, RNA, rep1 NpatKI, dTAG, 3hr, RNA,
GSM8223536 NpatKI, dTAG, 3hr, RNA, rep2 NpatKI, dTAG, 3hr, RNA,
GSM8223537 NpatKI, dTAG, 3hr, RNA, rep3 NpatKI, dTAG, 3hr, RNA,

Datasets on a similar topic

GSE264594 The XPO7-NPAT axis represents key vulnerabilities in TP53-mutated acute myeloid leukemia (ATAC-Seq) 9 samples shares xpo7-npat, vulnerabilities, tp53-mutated, represents, leukemia, myeloid, acute
GSE313357 Hippocampal estrogen levels, receptor types and epigenetics contribute to sex-specific memory-vulnerabilities to concurrent acute stresses [RNA-Seq] 9 samples shares vulnerabilities, rna-seq, acute
GSE327228 RNA Terminal Uridylyl-Transferases Are Druggable Vulnerabilities in AML, but are Dispensable for Normal Hematopoiesis [RNA-seq] 27 samples shares vulnerabilities, rna-seq
GSE254388 CDK12 Loss Promotes Prostate Cancer Development While Exposing Vulnerabilities to Paralog-Based Synthetic Lethality [RNA-Seq] 14 samples shares vulnerabilities, rna-seq
GSE301491 Transient YAP/TAZ inhibition exposes therapeutic vulnerabilities in advanced cancers [RNA-Seq] 8 samples shares vulnerabilities, rna-seq
GSE240460 Molecular Plasticity Results in Oncofetal Reprogramming and Therapeutic Vulnerabilities in Juvenile Myelomonocytic Leukemia 6 samples shares vulnerabilities, leukemia
GSE254387 CDK12 Loss Promotes Prostate Cancer Development While Exposing Vulnerabilities to Paralog-Based Synthetic Lethality [scRNA-Seq] 6 samples shares vulnerabilities, rna-seq
GSE301495 Transient YAP/TAZ inhibition exposes therapeutic vulnerabilities in advanced cancers [scRNA-Seq 2] 4 samples shares vulnerabilities, rna-seq

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