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Circulating transcriptome analysis finds gene signatures and immune cell activation and abundance predict response to immunotherapy in bladder cancer

GSE307931 Homo sapiens (human) RNA-seq (gene expression) 164 samples Submitted 2025/12/12 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 164 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
Bladder cancerThis series is part of our curated briefing on it.
Samples
164 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
Circulating Transcriptome Analysis Finds Gene Signatures and Immune Cell Activation and Abundance Predict Response to Immunotherapy in Bladder CancerClinical cancer research : an official journal of the American Association for Cancer Research · 2026
Summary (written by the submitters)
Background. Immune Checkpoint Blockers (ICB) have revolutionized oncology by achieving durable tumor responses in advanced cancers. Nevertheless, currently approved biomarkers (PD-L1, MSI, TMB) have suboptimal positive and negative predictive values for tumor response and survival. Patients and Methods. We aimed to assess the value of RNA sequencing from circulating blood, a new type of liquid biopsy, to predict responses to ICB.
Read the full summary ↓
We performed total paired-end RNA sequencing at 20 million reads and analyzed differential gene expression, signaling pathway activation, and immune cell abundances according to cancer outcomes. The analysis was conducted on baseline frozen whole blood samples from 164 patients prospectively enrolled in the IOPREDI study. Results. We found that some immune-related genes and signaling pathways were highly expressed in patients who achieved a durable clinical benefit. Furthermore, analyses of both progression-free survival (PFS) and overall survival (OS) confirmed significantly higher expression levels of immune-related signaling pathways in long-term survivors. Gene expression signatures capable of classifying patients based on clinical response or PFS were also identified. Interestingly, deconvolution analysis revealed a significant higher abundance of resting NK cells in patients with prolonged PFS or OS, in contrast to other cytotoxic cell types. Finally, high expression of the CST7 gene and increased abundance of naïve B lymphocytes were associated with immune-related adverse events (irAEs). Conclusion. Total RNA sequencing from whole blood provides high-quality data to predict clinical response, survival, and occurrence of irAEs. The use of this liquid biopsy prior to immune checkpoint blockage could improve treatment efficacy and irAEs management.
Published in
Circulating Transcriptome Analysis Finds Gene Signatures and Immune Cell Activation and Abundance Predict Response to Immunotherapy in Bladder Cancer
Chevrier S, Richard C, Adotévi O et al. · Clinical cancer research : an official journal of the American Association for Cancer Research 2026 · PMID 41528984 · doi:10.1158/1078-0432.CCR-25-2306
This dataset
Open GSE307931 in finder → Find more human RNA-seq datasets → Bladder cancer 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 GSE307931_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 PRJNA1327844 and SRA study SRP619729. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41528984) ↗
Study design
A cohort of 164 individual samples

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

How we read this: Sample titles run E2302005 … E2319041 and carry no group information.

Samples in this study

+ 124 more — browse all 164 samples with per-sample file links →

More Bladder cancer 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.