← BioTransfer GEO Dataset Finder
GEO series

IL-17–Driven Tumor Cell–Intrinsic Inflammatory Programming Creates an Immunotherapy-Permissive Microenvironment

GSE319592 Mus musculus (mouse) Single-cell RNA-seq 12 samples Submitted 2026/07/02 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 12 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
Mus musculus (mouse)
Samples
12 samples
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
IL-17-driven tumor cell-intrinsic inflammatory programming creates an immunotherapy-permissive microenvironmentMolecular cancer · 2026
Summary (written by the submitters)
Ovarian clear cell carcinoma (OCCC) is a chemoresistant subtype of ovarian cancer with limited effective therapeutic options. Although immune checkpoint inhibitors (ICIs) have shown little benefit in unselected ovarian cancer populations, clinical activity observed in a subset of OCCC patients suggests the presence of a histotype-specific immune vulnerability that remains poorly defined.
Read the full summary ↓
To elucidate this biology, we integrated transcriptomic analyses from multiple independent human OCCC cohorts with immunohistochemical profiling and mechanistic studies using an immunocompetent syngeneic OCCC mouse model. Tumor cell–intrinsic and microenvironmental responses to IL-17 were investigated through in vitro stimulation assays, in vivo IL-17 administration, single-cell RNA sequencing of tumor-infiltrating T cells, and immune checkpoint blockade in a Th17-biased partial chimera model. OCCC was characterized as an IL-6–high tumor entity with a globally immune-sparse but CD4⁺ T-cell–skewed tumor immune microenvironment. Transcriptomic analyses identified a Th17-associated program marked by elevated RORC expression in a subset of tumors. Across large clinical cohorts, an IL17A^high subset demonstrated a T cell–inflamed gene expression profile independent of microsatellite instability and tumor mutational burden; however, this phenotype was not associated with survival in untreated disease. Mechanistically, IL-17 directly activated NF-κB–dependent inflammatory programs in OCCC tumor cells, inducing cytokines involved in T-cell recruitment and activation. In vivo, IL-17 remodeled the immune microenvironment, increasing infiltration and activation of both CD4⁺ and CD8⁺ T cells. Single-cell profiling further revealed expansion of Th17/Tfh-like CD4⁺ T cells and cytotoxic, non-terminally exhausted CD8⁺ T cells. Consistent with these findings, anti–PD-L1 therapy significantly improved survival exclusively in Th17-biased partial chimera mice. Collectively, these results demonstrate that a Th17-biased, IL-17–responsive immune contexture in OCCC engages tumor cell–intrinsic NF-κB inflammatory signaling to prime antitumor T-cell states and enable checkpoint blockade efficacy. This immune biology is predictive rather than prognostic, supporting a biomarker-driven immunotherapy strategy for OCCC within otherwise ICI-refractory ovarian cancer.
Published in
IL-17-driven tumor cell-intrinsic inflammatory programming creates an immunotherapy-permissive microenvironment
Murakami K, Takamura S, Miyagawa C et al. · Molecular cancer 2026 · PMID 42380903 · doi:10.1186/s12943-026-02726-2
This dataset
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.

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 GSE319592_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1423802 and SRA study SRP677182. Searching any of these in the dataset finder brings you back here.

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 12 more — browse all 12 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.