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Spatial biology reveals macrophage dysfunction in immunosuppressed non-melanoma skin cancer

GSE316922 Homo sapiens (human) Single-cell RNA-seq 36 samples Submitted 2026/08/07 Platform GPL34284
At a glance

Single-cell RNA-seq · human · 36 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
Homo sapiens (human)
Topic
MelanomaThis series is part of our curated briefing on it.
Samples
36 samples: 32 × S vs 2 × S132 vs 2 × S144Groups 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
Spatial biology reveals altered macrophage states in immunosuppressed non-melanoma skin cancerCell · 2026
Summary (written by the submitters)
The rising incidence of non-melanoma skin cancer (NMSC), including basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC), particularly among immunosuppressed individuals, underscores the need for a deeper understanding of the tumor microenvironment (TME) to develop effective and safe immunotherapies. This study employed single-cell multi-omic analyses to investigate the spatial distribution and transcriptional profiles of immune cells in NMSC from both immunocompetent (IC) and immunosuppressed (IS) patients.
Read the full summary ↓
Our results challenge the prevailing notion that immunosuppression is primarily driven by reduced immune cell abundance or lymphocytic dysfunction. We found that IS tumors retain all requisite immune cell populations but display functional suppression and disrupted spatial organization. Our data revealed a limited number of distinct programs, particularly in macrophages and their spatially organized niches, that are linked to restricted T-cell repertoire diversity and impaired clonal expansion, providing a mechanistic bridge between innate dysfunction and adaptive immune failure. These perturbations were further confirmed by a novel spatial epigenomic atlas of the NMSC TME that revealed immune status–specific regulatory programs, including MAF- and ATF3-driven macrophages and CUX1- enriched fibroblast niches, that shape the epigenetic landscape of immunosuppressed tumors. These findings highlight the central role of innate immunity in shaping anti-tumor responses and offer potential therapeutic targets to enhance immunotherapy in this vulnerable patient population.
Published in
Spatial biology reveals altered macrophage states in immunosuppressed non-melanoma skin cancer
Naara S, Kochat V, Rao X et al. · Cell 2026 · PMID 42556334 · doi:10.1016/j.cell.2026.07.031
This dataset
Open GSE316922 in finder → Find more human RNA-seq datasets → Melanoma 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 GSE316922_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 PRJNA1405546 and SRA study SRP664747. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42556334) ↗
Study design
32 × S vs 2 × S132 vs 2 × S144

Supports a between-group comparison across 36 samples.

How we read this: 3 replicated groups read from 36 sample titles; they account for 36 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
More Melanoma datasets

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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.