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Transient YAP/TAZ inhibition exposes therapeutic vulnerabilities in advanced cancers [ATAC-seq]

GSE301500 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 11 samples Submitted 2026/06/17 Platform GPL19057
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 11 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
11 samples: 6 × [ATAC-Seq] shYT#2 vs 5 × [ATAC-Seq] shRenGroups 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.
Summary (written by the submitters)
YAP and TAZ, key effectors of the Hippo pathway, are frequently hyperactivated in cancer, where they drive tumor progression and resistance to therapy. Their oncogenic activity relies on interaction with TEAD transcription factors, making the TEAD-YAP/TAZ complex an attractive therapeutic target. Using translational mouse models, we demonstrate that sustained systemic YAP/TAZ depletion leads to severe side effects.
Read the full summary ↓
However, even transient YAP/TAZ inhibition alone is sufficient to suppress tumor growth in advanced stages. Mechanistically, YAP/TAZ activity promotes T cell exclusion from the tumors by inducing target genes involved tissue remodelling. Consequentially, YAP/TAZ inhibition induces immune infiltration, but the infiltrating T cells rapidly become exhausted. Combining YAP/TAZ inhibition with immune checkpoint blockade (ICB) overcomes this exhaustion and sensitizes previously resistant tumors to immunotherapy.
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 GSE301500_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1285344 and SRA study SRP597423. Searching any of these in the dataset finder brings you back here.

Study design
6 × [ATAC-Seq] shYT#2 vs 5 × [ATAC-Seq] shRen

Supports a between-group comparison across 11 samples.

How we read this: 2 replicated groups read from 11 sample titles; they account for 11 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
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