← BioTransfer GEO Dataset Finder
GEO series

YTHDF2 promotes ATP synthesis and immune evasion in B cell malignancies

GSE247936 Mus musculus (mouse) Single-cell RNA-seq 46 samples Submitted 2024/12/16 Platform GPL24676Platform GPL24247Platform GPL16791
At a glance

Single-cell RNA-seq · mouse · 46 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Mus musculus (mouse)
Samples
46 samples: 16 conditions, mostly in duplicateGroups 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
YTHDF2 promotes ATP synthesis and immune evasion in B cell malignanciesCell · 2025
Summary (written by the submitters)
RNA epigenetics plays crucial roles in physiological and pathological processes. As the most abundant methylation of mRNA, 0.2-0.7% of the total adenosine, m6A is dynamically deposited co-transcriptionally by the methyltransferase complex, reversely removed by demethylases recognized and directly regulated by “reader” proteins.
Read the full summary ↓
As the first identified m6A ‘reader’ protein, YTHDF2 recognizes and destabilizes m6A modified mRNAs by inducing mRNA decay or degradation in P-body and plays indispensable oncogenic or tumor suppressive roles in multiple malignant contexts by mediating distinct m6A modified mRNAs. Here, we report that YTHDF2 promotes the development of B cell malignancies by facilitating energy supplements and immune evasion. RNA-sequencing (RNA-seq) data reveal that a set of ATP production- and immune response-related genes are consistently and significantly dysregulated upon YTHDF2 knockdown (KD) in both B cell acute lymphoblastic leukemia (B-ALL) patient-derived xenotransplant (PDX) cells (IAH8R) and diffuse large B cell lymphoma (DLBCL) cells (SU-DHL-4). RNA immunoprecipitation sequencing (RIP-seq) of either wildtype or mutant YTHDF2 proteins identify target genes directly bind to YTHDF2 dependent on the RNA binding pockets. Methylation RIP-seq (MeRIP-seq) assays identify either m6A-moidfied genes or m5C-modified mRNAs, which is further confirmed by bisulfite-converted mRNA sequencing (BS-RNA-seq) in malignant B cells. Mechanically, we find that YTHDF2 enhances ATP synthesis by sustaining mRNA stabilities of target genes as an m5C reader protein by interacting with PABPC1, a well-know m5C-modified mRNA stabilizer. Further RNA-seq upon PABPC1 KD and RIP-seq assays for PABPC1 reveal the overlapped genes which are also regulated and bound with YTHDF2 via m5C modification. Strikingly, RNA-seq and m6A-MeRIP-seq data show that YTHDF2 promotes immune evasion by destabilizing CD19 and MHC-II molecules (e.g., HLA-DMA and HLA-DMB) in an m6A-dependent manner. Single cell RNA-seq (scRNA-seq) data further reveal the immune microenvironment and cell proportions in bone marrow of Ythdf2 conditional KO mouse models (Ythdf2fl/fl). Our proof-of-concept study discovers that a YTHDF2 selective inhibitor (e.g. CCI-38) significantly inhibits cell metabolism and immune evasion in malignant B cells (KOPN-8) by RNA-seq. Collectively, our data show that YTHDF2 promotes ATP synthesis and immune evasion and serves as a promising therapeutic target in B cell malignancies.
Published in
YTHDF2 promotes ATP synthesis and immune evasion in B cell malignancies
Chen Z, Zeng C, Yang L et al. · Cell 2025 · PMID 39694037 · doi:10.1016/j.cell.2024.11.007
This dataset
Open GSE247936 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 GSE247936_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1040931 and SRA study SRP472264. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39694037) ↗
Study design
16 conditions, mostly in duplicate
IAH8R-flag-PABPC1-IP ×3 IAH8R-shYTHDF2-1 ×2 IAH8R-shYTHDF2-2 ×2 IAH8R-shPABPC1-1 ×2 IAH8R-shPABPC1-2 ×2 KOPN-8-DMSO ×2 KOPN-8-CCI-38 ×2 IAH8R-m6A-IP ×2 +21 more

Supports a between-group comparison across 33 samples.

How we read this: 16 replicated groups read from 46 sample titles; they account for 33 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

+ 6 more — browse all 46 samples with per-sample file links →

Datasets on a similar topic

Search all 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.