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ALKBH1-mediated tRNA 5-formylcytidine modification facilitates codon-biased translation and leukemogenesis [RNA-seq]

GSE260905 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/07/23 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 12 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 myeloid leukemiaThis series is part of our curated briefing on it.
Samples
12 samples: 3 × MOLM13_shNS_DMSO vs 3 × MOLM13_shNS_Venetoclax vs 3 × MOLM13_shALKBH1_DMSO vs 3 × MOLM13_shALKBH1_VenetoclaxGroups 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
ALKBH1 Drives Tumorigenesis and Drug Resistance via tRNA-decoding Reprogramming and Codon-biased TranslationCancer discovery · 2025
Summary (written by the submitters)
Here, we show that ALKBH1 is overexpressed in acute myeloid leukemia (AML) and required for AML development/maintenance and leukemia stem cell (LSC) self-renewal, but is dispensable for normal hematopoiesis. ALKBH1 plays a pivotal role in regulating mitochondrion structure/functions and facilitating oxidative phosphorylation (OXPHOS) to generate energy for AML cell survival/proliferation.
Read the full summary ↓
Mechanistically, we uncover that ALKBH1 specifically promotes 5-formylcytidine (f5C) formation in tRNAs to expand tRNA decoding capacity and promote translation of essential targets. This mechanism/phenomenon is termed “epitranscriptomic Midas touch”, which promotes expression of WDR43 and BCL2, two crucial targets of ALKBH1 in AML. ALKBH1 targeting markedly enhances BCL2 inhibitor (Venetoclax)’s efficacy in AML treatment. Collectively, our studies reveal the functional importance of a previously unappreciated signaling (i.e., ALKBH1/tRNA-f5C/WDR43/BCL2) in AML, and highlight the potential of targeting ALKBH1 for cancer therapy.
Published in
ALKBH1 Drives Tumorigenesis and Drug Resistance via tRNA-decoding Reprogramming and Codon-biased Translation
Shen C, Che Y, Zhou K et al. · Cancer discovery 2025 · PMID 40747882 · doi:10.1158/2159-8290.CD-24-1043
This dataset
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.

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 GSE260905_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1083976 and SRA study SRP493446. Searching any of these in the dataset finder brings you back here.

Study design
3 × MOLM13_shNS_DMSO vs 3 × MOLM13_shNS_Venetoclax vs 3 × MOLM13_shALKBH1_DMSO vs 3 × MOLM13_shALKBH1_Venetoclax

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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 myeloid leukemia datasets

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