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Analysis of transcriptomic and epitranscriptomic effects of the acute megakaryoblastic leukemia fusion protein RBM15-MKL1

GSE275299 Homo sapiens (human) RNA-seq (gene expression) 71 samples Submitted 2025/05/16 Platform GPL21103Platform GPL24247Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 71 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
71 samples: 69 distinct titles, 2 of them repeatedGroups 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
RBM15-MKL1 fusion protein promotes leukemia via m6A methylation and Wnt pathway activationBlood · 2025
Summary (written by the submitters)
The RBM15-MKL1 (RM) fusion protein causes acute megakaryoblastic leukemia (AMKL) primarily in infants. RBM15 recruits the m6A writer complex and is essential for determining the m6A epitranscriptome. MKL1 is a transcriptional cofactor important to megakaryopoiesis. Although the functions of the component proteins are well described, the mechanism whereby the RM fusion protein induces AMKL is unknown.
Read the full summary ↓
We performed a high-resolution multi-omics analysis to identify the direct transcriptional, RNA-binding, and epitranscriptional targets of RM compared to RBM15. While RM maintains the RNA-binding and m6A modification capabilities of wildtype RBM15, it also has distinct RNA targets, many of which are upregulated and stabilized in RM-expressing cells. Among the top targets that are differentially bound, m6A modified, and upregulated by RM are the Frizzled genes, which encode receptors for the Wnt signalling pathway. To assess the role of RM-mediated m6A modifications in a physiologically relevant model, we treated two murine AMKL cell lines with STM3675, a novel METTL3 inhibitor. In vitro, METTL3 inhibition causes murine AMKL cells to undergo differentiation and apoptosis. In vivo treatment with METTL3 inhibitor prolongs survival of mice transplanted with murine AMKL cells. We additionally show that treatment with STM3675 decreases expression of key RM target genes, including Frizzled genes. Knockdown of Frizzled genes in RM-driven murine AMKL cells decreases their growth and survival, suggesting that RM-specific binding, m6A modification, and aberrant upregulation of the Wnt signaling pathway contribute to leukemogenesis and may represent targetable therapeutic pathways for treatment of children with RM-AMKL.
Published in
RBM15-MKL1 fusion protein promotes leukemia via m6A methylation and Wnt pathway activation
Mayday MY, Biancon G, Wei M et al. · Blood 2025 · PMID 40435410 · doi:10.1182/blood.2024027712
This dataset
Open GSE275299 in finder → Find more 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 GSE275299_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 PRJNA1150216 and SRA study SRP527605. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40435410) ↗
Study design
69 distinct titles, 2 of them repeated
RNAseq, primary murine MKP, ×2 RNAseq, primary murine ERP, ×2

How we read this: Read from 71 sample titles: 69 distinct titles with little repetition. 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

+ 31 more — browse all 71 samples with per-sample file links →

Datasets on a similar topic

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