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Dysregulation of the Hippo Pathway in Cancer Associated Fibroblasts is Associated with anti-PD-L1 atezolizumab Resistance

GSE313827 Homo sapiens (human) Single-cell RNA-seq 18 samples Submitted 2026/02/20 Platform GPL34284
At a glance

Single-cell RNA-seq · human · 18 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)
Samples
18 samples: 6 conditions, mostly in triplicateGroups 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
The Hippo Pathway Is Dysregulated in Cancer-Associated Fibroblasts in Anti-PD-L1-Resistant CancerCancer research · 2026
Summary (written by the submitters)
The use of immunotherapy in solid tumors has significantly improved the outcomes and quality of life for cancer patients. However, a substantial fraction of patients remain unresponsive, highlighting the urgent need to identify novel mechanisms of resistance to enhance immune-centric, chemo-free treatment regimens.
Read the full summary ↓
In this study, we investigate associations with immunotherapy resistance by integrating RNAseq data from 2800 bladder cancer patients enrolled in the IMvigor trials, focusing on resistance to the anti-PD-L1 therapy atezolizumab, along with single-cell data from 200 patient samples and healthy donors. To expand the analysis to a massive collection of over 100M cells from hundreds of diverse single cell studies, we present Firmament, a newly developed method to efficiently identify cell populations that show enrichment for expression of gene signatures. Through these analyses, we identify the Hippo pathway as critically associated with immunotherapy resistance in bladder cancer and other solid tumors. Our findings indicate that Hippo dysregulation in stromal cells, rather than cancer cells, drives the high YAP/TAZ signal in these tumors. We specifically identify dysregulated Hippo signaling in cancer-associated fibroblasts compared to healthy donor fibroblasts. These insights will be important for developing novel therapeutic combinations to improve outcomes for patients with solid tumors treated with immune checkpoint inhibitors.
Published in
The Hippo Pathway Is Dysregulated in Cancer-Associated Fibroblasts in Anti-PD-L1-Resistant Cancer
Roels J, Ghaedi H, Kancherla J et al. · Cancer research 2026 · PMID 41784658 · doi:10.1158/0008-5472.CAN-24-3954
This dataset
Open GSE313827 in finder → Find more human RNA-seq datasets →
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 GSE313827_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 PRJNA1381646 and SRA study SRP655320. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41784658) ↗
Study design
6 conditions, mostly in triplicate
human.lung.CAF.DMSO ×3 human.lung.CAF.1.uM.TEADi ×3 human.lung.CAF.3.uM.TEADi ×3 human.PDAC.CAF.DMSO ×3 human.PDAC.CAF.1.uM.TEADi ×3 human.PDAC.CAF.3.uM.TEADi ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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
Datasets on a similar topic

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