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Opposing tumor cell-intrinsic and -extrinsic roles of the IRF1 transcription factor in anti-tumor immunity

GSE246923 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 49 samples Submitted 2024/05/01 Platform GPL24247Platform GPL21493Platform GPL21290
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 49 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
49 samples: 13 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
Opposing tumor-cell-intrinsic and -extrinsic roles of the IRF1 transcription factor in antitumor immunityCell reports · 2024
Summary (written by the submitters)
Type I interferons (IFN-I) and IFN- foster antitumor immunity by facilitating T cell responses. Paradoxically, IFNs may promote T cell exhaustion by activating immune checkpoints. The downstream regulators of these responses are incompletely understood. Herein, we describe how Interferon Regulatory Factor 1 (IRF1) orchestrates these opposing effects of IFNs.
Read the full summary ↓
IRF1 expression in tumors blocked Toll-like receptor and IFN-I-dependent host antitumor immunity by preventing IFN stimulated gene (ISG) programs and effector programs in dendritic cells and T cells. In contrast, expression of IRF1 in the host, but not IRF3 or IFN-, was also required for antitumor immunity to wildtype and Irf1-/- tumors. Mechanistically, tumor cell IRF1 regulated major histocompatibility class I expression and bound uniquely or together with STAT1 at many ISGs, contributing to expression of immunosuppressive but not immunostimulatory ISGs. Overexpression of PD-L1 in Irf1-/- tumors only partially restored tumor growth, suggesting that the negative effects of tumor IRF1 on antitumor immunity are multifactorial. Thus, we identify tumor cell IRF1 expression as a previously unrecognized selective inhibitor of host IFN-I dependent antitumor immunity, while host IRF1 and IFN-I are critical drivers of antitumor immune responses.
Published in
Opposing tumor-cell-intrinsic and -extrinsic roles of the IRF1 transcription factor in antitumor immunity
Purbey PK, Seo J, Paul MK et al. · Cell reports 2024 · PMID 38833371 · doi:10.1016/j.celrep.2024.114289
This dataset
Open GSE246923 in finder → Find more ChIP / ATAC / CUT&Tag 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 GSE246923_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1035108 and SRA study SRP469972. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38833371) ↗
Study design
13 conditions, mostly in duplicate
WT_MC38, IRF1, ChIP-seq, ×4 IRF1KO_MC38, IRF1, ChIP-seq, ×4 WT_MC38, STAT1, ChIP-seq, ×4 IRF1KO_MC38, STAT1, ChIP-seq, ×4 WT_MC38_2h-IFNG, mRNA-Seq, clone ×3 Input ×2 WT_MC38, untreated, mRNA-Seq, clone ×2 IRF1KO_MC38_untreated, mRNA-Seq, clone ×2 +19 more

Supports a between-group comparison across 35 samples.

How we read this: 13 replicated groups read from 49 sample titles; they account for 35 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

+ 9 more — browse all 49 samples with per-sample file links →

Datasets on a similar topic

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