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RNA exonuclease REXO4 resolves m6A-marked R-loops and suppresses anti-tumor immunity [RNAseq]

GSE289625 Mus musculus (mouse) RNA-seq (gene expression) 28 samples Submitted 2026/05/28 Platform GPL24676Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 28 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
28 samples: 10 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)
Transcription blockage frequently occurs in tumor cells, and aberrant R-loop forming during this process drives genome instability. However, the regulation of R-loop homeostasis and its dysregulation in tumorigenesis are still under investigation. Here, we report that the RNA exonuclease REXO4 preserves genome stability by reducing excessive R-loops.
Read the full summary ↓
Mechanistically, REXO4 resolves R-loops by 3’-5’ exonucleolytic cleavage of the RNA strand on RNA-DNA hybrids, where an accessible end is created by RNA endonuclease and N6-methyladenosine (m6A) modification on RNA moieties promotes REXO4 localization and R-loop removal. REXO4 ablation-induced DNA damage stimulates interferon response and tumor immune infiltration to suppress squamous cell carcinoma (SCC) growth and metastasis. Importantly, targeting the exonuclease activity of REXO4 via the inhibitor we developed synergizes with PD-1 blockade to inhibit SCC progression by recruiting and activating CD8+ T cells. Thus, our study provides mechanistic insight into how m6A couples with exonuclease in R-loop clearance and genome maintenance, and uncovers a druggable epi-transcriptional machinery that blocks innate immune response and enables SCC immune evasion.
This dataset
Open GSE289625 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 GSE289625_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 PRJNA1223845 and SRA study SRP563981. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
10 conditions, mostly in triplicate
SCC1_Ctrl_Vehicle ×3 SCC1_H151_iR4 ×3 SCC1_iR4 ×3 SCC1_KO_2_BX_795 ×3 SCC1_KO_2_H151 ×3 SCC1_R4KO_1_Vehicle ×3 SCC1_R4KO_2_Vehicle ×3 SCC1_Vehicle ×3 +2 more

Supports a between-group comparison across 28 samples.

How we read this: 10 replicated groups read from 28 sample titles; they account for 28 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
Datasets on a similar topic

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