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Divergent Macrophage-Regulated T cell States Determine Response to Bacillus Calmette-Guérin (BCG) in High-Risk Bladder Cancer

GSE322495 Homo sapiens (human) Single-cell RNA-seq 21 samples Submitted 2026/03/30 Platform GPL34284
At a glance

Single-cell RNA-seq · human · 21 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
Bladder cancerThis series is part of our curated briefing on it.
Samples
21 samples: 7 × Bladder tissue and PBMC, BCG unresponsive, sample vs 7 × Bladder tissue and PBMC, BCG naïve, sample vs 6 × Bladder tissue and PBMC, BCG responsive, sampleGroups 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
Divergent macrophage-regulated T cell states determine response to Bacillus Calmette-Guérin vaccine in high-risk bladder cancerThe Journal of clinical investigation · 2026
Summary (written by the submitters)
The primary therapy for high-risk bladder cancer (BCa) is repeated instillations of the tuberculosis vaccine, Bacillus Calmette-Guerin (BCG). While BCG decreases the risk of recurrence by more than half, the concerted mechanisms of immune activation from BCG are unknown. Our objective was to investigate how the immune response differs between responders and non-responders to BCG therapy.
Read the full summary ↓
We performed single-cell RNA-sequencing of isolated immune cells adjacent to high-risk bladders before and after BCG in BCG responders and non-responders. We identify an increase in Th17-like Th1 cells in BCG responders, characterized by greater expression of pro-inflammatory cytokines. Alternatively, non-responders had increased CD8+ T-cell exhaustion and T-regulatory cells. We identify that the primary mechanism of divergent T cell activity is driven by altered polarization and immunosuppressive signaling with myeloid cells. Through a machine-learning-based approach, we identified a Th17-like Th1 cytokines, such as IL17, IL21, and IL26, were predictive of a response, which were then validated in a separate BCG-treated BCa cohort. Together, this suggests that dynamic regulation of myeloid-T cell interactions can be targeted to improve BCG activity.
Published in
Divergent macrophage-regulated T cell states determine response to Bacillus Calmette-Guérin vaccine in high-risk bladder cancer
Brown RJ, Khan MT, Houston AJ et al. · The Journal of clinical investigation 2026 · PMID 42081487 · doi:10.1172/JCI200442
This dataset
Open GSE322495 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 GSE322495_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 PRJNA1429460 and SRA study SRP679910. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42081487) ↗
Study design
7 × Bladder tissue and PBMC, BCG unresponsive, sample vs 7 × Bladder tissue and PBMC, BCG naïve, sample vs 6 × Bladder tissue and PBMC, BCG responsive, sample

Supports a between-group comparison across 20 samples.

How we read this: 3 replicated groups read from 21 sample titles; they account for 20 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 Bladder cancer datasets

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