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ATR inhibition induces NF-κB-dependent immunogenicity in Merkel cell carcinoma independent of cGAS-STING

GSE317774 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2026/01/27 Platform GPL28038
At a glance

RNA-seq (gene expression) · human · 48 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
Merkel cell carcinomaThis series is part of our curated briefing on it.
Samples
48 samples: 48 samples, each with a distinct title — no replicated groupsGroups 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)
There is an urgent unmet need to develop novel therapeutic strategies for tumors that do not respond to immune checkpoint inhibition (ICI) via PD-1 pathway blockade. The ATR-mediated DNA replication checkpoint has been reported to have immune-augmenting properties; however, the mechanisms underlying these properties are not well characterized.
Read the full summary ↓
Here we explore the potential immunogenic effects of ATR inhibition in Merkel cell carcinoma (MCC), a cancer that is particularly relevant due to its high proliferative index and frequent response to anti-PD-(L)1 therapy. ATR inhibition induced tumor cell cytotoxicity in both Merkel cell polyomavirus-positive and UV-induced MCC cell lines in the absence of exogenous DNA damage. ATR inhibition alone or in combination with low-dose radiation induced numerous proinflammatory TNF-NF-κB signals as assessed via bulk transcriptomic profiling. These included increased expression of MHC class-I alleles, antigen processing machinery, interleukins, chemokines and interferon genes associated with anti-tumor immune responses in diverse tumor types. In parallel, we observed enhanced surface exposure of the “eat-me” signal calreticulin on MCC cells and subsequent phagocytosis by human monocyte-derived macrophages. Given that MCC tumors are often cGAS-STING-deficient (including two cell lines examined here), these ATRi-induced mechanisms are significant as they were activated regardless of cGAS-STING functional status. These data provide a mechanistic basis for the clinical evaluation of ATRi in advanced ICI-refractory MCC (NCT05947500), and suggest biomarkers that may be associated with response in human MCC tumors treated with ATRi.
This dataset
Open GSE317774 in finder → Find more human RNA-seq datasets → Merkel cell carcinoma landscape →
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 GSE317774_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 PRJNA1415218 and SRA study SRP667869. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
48 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 48 sample titles: 48 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

+ 8 more — browse all 48 samples with per-sample file links →

More Merkel cell carcinoma datasets

Search all human RNA-seq datasets in GEO →

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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.