← BioTransfer GEO Dataset Finder
GEO series

Disrupting tRNA modifications to target mitochondrial vulnerabilities in drug-resistant leukemia cells

GSE228208 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2025/08/19 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 48 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
48 samples: 16 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
Disrupting tRNA modifications to target mitochondrial vulnerabilities in drug-resistant leukemia cellsBlood · 2025
Summary (written by the submitters)
To comprehensively identify cancer-relevant RNA modifications and their regulators, we screened all 150 known human RNA modifying proteins across 18 different normal and cancer lines using a CRISPR-based genetic knockout system.
Published in
Disrupting tRNA modifications to target mitochondrial vulnerabilities in drug-resistant leukemia cells
Pauli C, Kienhöfer M, Blank MF et al. · Blood 2025 · PMID 40749163 · doi:10.1182/blood.2024027822
This dataset
Open GSE228208 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 GSE228208_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 PRJNA948814 and SRA study SRP429335. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40749163) ↗
Study design
16 conditions, mostly in triplicate
A2058 cells, biol ×3 A375 cells, biol ×3 A549 cells, biol ×3 Cal33 cells, biol ×3 FaDu cells, biol ×3 Kasumi-1 cells, biol ×3 MOLM13 cells, biol ×3 Normal human epdermal keratinocytes, biol ×3 +8 more

Supports a between-group comparison across 48 samples.

How we read this: 16 replicated groups read from 48 sample titles; they account for 48 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.