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BRAF inhibition increases TGFb2 production and stimulates metastasis in mice with endogenous BRAFV600E-induced hepatocellular carcinoma

GSE286241 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2025/12/04 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 12 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
Mus musculus (mouse)
Samples
12 samples: 12 samples, each with a distinct title — no replicated groupsGroups 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
BRAF inhibition increases TGFβ2 production and stimulates metastasis in mice with endogenous BRAF(V600E)-induced hepatocellular carcinomaProceedings of the National Academy of Sciences of the United States of America · 2025
Summary (written by the submitters)
Background & Aims: The MEK-ERK pathway plays a crucial role in hepatocellular carcinoma (HCC) pathogenesis, and BRAF mutations can contribute to its activation. While BRAF mutations, particularly BRAFV600E, are rare in human HCC, their effects when expressed physiologically in liver cells, especially in combination with high-incidence co-mutations in tumor suppressor genes, remain poorly understood in immunocompetent mouse models.
Read the full summary ↓
Moreover, the impact of BRAF inhibitors on HCC progression, especially metastasis, is not well-defined. Here, we study the role of endogenous BRAFV600E expression in liver tumorigenesis and the effect of RAF inhibition on progression and metastasis.
Published in
BRAF inhibition increases TGFβ2 production and stimulates metastasis in mice with endogenous BRAF(V600E)-induced hepatocellular carcinoma
Cisowski J, El Zowalaty AE, Sayin SI et al. · Proceedings of the National Academy of Sciences of the United States of America 2025 · PMID 41196356 · doi:10.1073/pnas.2503044122
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 GSE286241_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 PRJNA1208463 and SRA study SRP556329. Searching any of these in the dataset finder brings you back here.

Study design
12 samples, each with a distinct title — no replicated groups

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

How we read this: Read from 12 sample titles: 12 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
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