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Covalent pan-TEAD inhibitors block YAP activity and demonstrate brain penetrance in Hippo-dependent cancer models [Quant-seq]

GSE305227 Homo sapiens (human) RNA-seq (gene expression) 149 samples Submitted 2026/05/07 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 149 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)
Samples
149 samples: 120 distinct titles, 10 of them repeatedGroups 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)
TEAD proteins are a family of transcription factors that enable the oncogenic activity of deregulated Hippo signaling and are a promising therapeutic target in oncology. Targeting the lipid pocket of TEAD is an established path to inhibit the oncogenic activities of the cofactors YAP and TAZ. Here we present two covalent pan-TEAD inhibitors that bind to the lipid pocket, GNE-8025 and GNE-2181.
Read the full summary ↓
GNE-8025 binds TEAD proteins covalently at a conserved cysteine residue to engage the lipid pocket and allosterically disrupt the interaction of TEAD proteins with YAP. GNE-2181 is a further optimized version of GNE-8025 with properties that enable brain penetrance in vivo. Both of these small molecules suppress the proliferation of YAP-driven tumor cells both in vitro and in vivo and increase activity of a broad range of inhibitors of the MAPK pathway. We demonstrate that these molecules have exceptional efficacy in Hippo-driven in vivo tumor models, including in a mouse model of brain metastases where GNE-2181 treatment significantly inhibits the growth of intracranial brain tumors. Altogether we present a next-generation class of TEAD inhibitors. The development of GNE-8025 and GNE-2181 is a significant advancement towards potent, specific, and effective Hippo-targeting cancer therapies.
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 GSE305227_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: 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 PRJNA1304868. Searching any of these in the dataset finder brings you back here.

Study design
120 distinct titles, 10 of them repeated
NGS4532 BP043209 ES-2 DMSO, ×8 NGS4532 BP043210 NCI-H226 DMSO, ×4 NGS4532 BP045307 NCI-H226 DMSO, ×4 NGS4532 BP045308 NCI-H226 DMSO, ×4 NGS4532 BP045309 ES-2 DMSO, ×4 NGS4532 BP045309 NCI-H358 DMSO, ×4 NGS4532 BP043210 NCI-H358 DMSO, ×3 NGS4532 BP045307 NCI-H358 DMSO, ×3 +2 more

How we read this: Read from 149 sample titles: 120 distinct titles with little repetition. 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

+ 109 more — browse all 149 samples with per-sample file links →

Datasets on a similar topic

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.