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Cancer-induced nerve injury promotes resistance to anti-PD-1 therapy [RNA-Seq FFPE]

GSE289743 Homo sapiens (human) RNA-seq (gene expression) 83 samples Submitted 2025/08/20 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 83 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
Cutaneous squamous cell carcinomaThis series is part of our curated briefing on it.
Samples
83 samples: 26 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
Cancer-induced nerve injury promotes resistance to anti-PD-1 therapyNature · 2025
Summary (written by the submitters)
Peri-neural invasion (PNI) is a well-established poor prognostic factor in multiple cancer types. However, the mechanisms driving the PNI's detrimental clinical effect remain elusive. Here, we provide clinical and mechanistic insights into PNI and cancer-induced injury of tumor-associated nerves (TANs) and their role in resistance to anti-PD-1 therapy.
Read the full summary ↓
Our work demonstrates that poor response to anti-PD-1 therapy in cutaneous squamous cell carcinoma (cSCC), melanoma, and gastric cancer is associated with PNI and TANs injury. Ultrastructural electron microscopy analysis reveals that direct contact between cancer cells and nerve fibers leads to cancer-induced nerve injury (CINI) via myelin degradation. Injured neurons respond by autonomously initiating an interleukin (IL)-6 and interferon (IFN) type I inflammatory response. This inflammatory response alters the immune activity in the peri-neural niche in melanoma, cSCC, and pancreatic adenocarcinoma, leading to an immuno-suppressive activity aimed at nerve healing and regeneration. As the tumor grows, the CINI burden increases, the inflammatory signal within the niche becomes chronic, and eventually skews the general immune tone within the tumor microenvironment to a suppressive and exhaustive state. The CINI-driven anti-PD-1 resistance can be reversed by targeting multiple steps in the CINI signaling process: denervating the tumor, conditional knockout of the transcription factor mediating the injury signal within neurons (cKO-Atf3), knockout of the IFN-a receptor signaling (Ifnar1-/-), or by combining anti-PD-1 and anti-IL-6-receptor blockade. Our findings demonstrate the direct immuno-regulatory roles of TANs and their therapeutic potential.
Published in
Cancer-induced nerve injury promotes resistance to anti-PD-1 therapy
Baruch EN, Gleber-Netto FO, Nagarajan P et al. · Nature 2025 · PMID 40836096 · doi:10.1038/s41586-025-09370-8
This dataset
Open GSE289743 in finder → Find more human RNA-seq datasets → Cutaneous squamous 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 GSE289743_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 PRJNA1224435 and SRA study SRP564228. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40836096) ↗
Study design
26 conditions, mostly in duplicate
P8485_RNA ×5 P1244_RNA ×4 P2060_RNA ×4 P7043_RNA ×4 P1065_RNA ×3 P1175_RNA ×3 P1178_RNA ×3 P1604_RNA ×3 +31 more

Supports a between-group comparison across 70 samples.

How we read this: 26 replicated groups read from 83 sample titles; they account for 70 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

+ 43 more — browse all 83 samples with per-sample file links →

More Cutaneous squamous cell carcinoma 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.