GEO series

RNA Terminal Uridylyl-Transferases Are Druggable Vulnerabilities in AML, but are Dispensable for Normal Hematopoiesis [RNA-seq]

GSE327228 Mus musculus (mouse) RNA-seq (gene expression) 27 samples Submitted 2026/06/24 Platform GPL24247Platform GPL21626

At a glance

RNA-seq (gene expression) · mouse · 27 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: 27 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.

Summary (written by the submitters)

Acute myeloid leukemia (AML) is an aggressive hematological malignancy arising from hematopoietic stem and progenitor cells (HSPCs). Current treatments often fail to eradicate AML; therefore, new therapeutic strategies are essential. Here, we reveal that RNA Terminal-Uridylyl-Transferase-Enzymes 4 and 7 (TUT4/7) are druggable therapeutic targets, whose genetic deletion suppresses AML growth, induces apoptosis and improves the survival in leukemic mouse models.

Read the full summary ↓

Notably, a pre-clinical TUT4/7 inhibitor promotes cell death in AML patient samples and synergizes with venetoclax. Mechanistically, TUT4/7 inactivation suppresses mevalonate pathway gene expression, compromising the cholesterol synthesis pathway. Current AML therapies often cause severe hematopoietic toxicity. Although Tut4/7 deletion results in inflammatory activation throughout the hematopoietic system, this is permissive to a normal lifespan and Tut4/7-deficiency does not compromise HSPC function. Together, these findings identify TUT4/7 as druggable targets, whose inactivation suppresses AML while sparing normal hematopoiesis. In combination with venetoclax this represents a promising therapeutic strategy.

This dataset

Open GSE327228 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 GSE327228_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 PRJNA1450008 and SRA study SRP689872. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

8 conditions, mostly in triplicate

Meis1Hoxa9_2266 ×5 Meis1Hoxa9_DMSO ×5 preLSC, WT, ×4 preLSC, cDKO, ×3 NPM1_FLT3-ITD_2266 ×3 MLL-AF9_FLT3-ITD_2266 ×3 NPM1_FLT3-ITD_DMSO ×2 MLL-AF9_FLT3-ITD_DMSO ×2

Supports a between-group comparison across 27 samples.

How we read this: 8 replicated groups read from 27 sample titles; they account for 27 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

GSM9651763 preLSC, WT, rep1 preLSC, WT,
GSM9651764 preLSC, WT, rep2 preLSC, WT,
GSM9651765 preLSC, WT, rep3 preLSC, WT,
GSM9651766 preLSC, WT, rep4 preLSC, WT,
GSM9651767 preLSC, cDKO, rep1 preLSC, cDKO,
GSM9651768 preLSC, cDKO, rep2 preLSC, cDKO,
GSM9651769 preLSC, cDKO, rep3 preLSC, cDKO,
GSM9797725 Meis1Hoxa9_2266_1 Meis1Hoxa9_2266
GSM9797726 Meis1Hoxa9_2266_2 Meis1Hoxa9_2266
GSM9797727 Meis1Hoxa9_2266_3 Meis1Hoxa9_2266
GSM9797728 Meis1Hoxa9_2266_4 Meis1Hoxa9_2266
GSM9797729 Meis1Hoxa9_2266_5 Meis1Hoxa9_2266
GSM9797730 Meis1Hoxa9_DMSO_1 Meis1Hoxa9_DMSO
GSM9797731 Meis1Hoxa9_DMSO_2 Meis1Hoxa9_DMSO
GSM9797732 Meis1Hoxa9_DMSO_3 Meis1Hoxa9_DMSO
GSM9797733 Meis1Hoxa9_DMSO_4 Meis1Hoxa9_DMSO
GSM9797734 Meis1Hoxa9_DMSO_5 Meis1Hoxa9_DMSO
GSM9797735 NPM1_FLT3-ITD_2266_1 NPM1_FLT3-ITD_2266
GSM9797736 NPM1_FLT3-ITD_2266_2 NPM1_FLT3-ITD_2266
GSM9797737 NPM1_FLT3-ITD_2266_3 NPM1_FLT3-ITD_2266
GSM9797738 NPM1_FLT3-ITD_DMSO_1 NPM1_FLT3-ITD_DMSO
GSM9797739 NPM1_FLT3-ITD_DMSO_2 NPM1_FLT3-ITD_DMSO
GSM9797740 MLL-AF9_FLT3-ITD_2266_1 MLL-AF9_FLT3-ITD_2266
GSM9797741 MLL-AF9_FLT3-ITD_2266_2 MLL-AF9_FLT3-ITD_2266
GSM9797742 MLL-AF9_FLT3-ITD_2266_3 MLL-AF9_FLT3-ITD_2266
GSM9797743 MLL-AF9_FLT3-ITD_DMSO_1 MLL-AF9_FLT3-ITD_DMSO
GSM9797744 MLL-AF9_FLT3-ITD_DMSO_2 MLL-AF9_FLT3-ITD_DMSO

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GSE311841 RNA Terminal Uridylyl-Transferases Are Druggable Vulnerabilities in AML, but are Dispensable for Normal Hematopoiesis 8 samples shares aml, uridylyl-transferases, vulnerabilities, hematopoiesis, dispensable, druggable, terminal
GSE248654 TAF1, the largest subunit of TFIID, is dispensable for adult hematopoiesis [RNA-Seq] 36 samples shares hematopoiesis, dispensable, rna-seq
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GSE274479 Non-Canonical PRC1.1 is required for the activity of Menin-MLL1 Inhibitors in NUP98-Rearranged AML [RNA-seq] 15 samples shares aml, rna-seq
GSE309162 P300/CBP inhibition with gilteritinib and venetoclax targets leukemia stem cells in epigenetic mutant AML [RNA-Seq] 12 samples shares aml, rna-seq
GSE264051 Dysregulated innate immune signaling cooperates with RUNX1 mutations to transform an MDS-like disease to AML (RNA-Seq) 12 samples shares aml, rna-seq
GSE269040 Dissecting tissue-specific microenvironments in acute myeloid leukemia (RNA-Seq VecadAML) 12 samples shares aml, rna-seq

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