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CCN6/WISP3 suppresses metaplastic breast carcinoma by antagonizing a WNT/b-catenin/EZH2 cascade [ChIP-seq]

GSE250574 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 16 samples Submitted 2024/07/10 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 16 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
16 samples: 16 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.
Summary (written by the submitters)
Metaplastic breast carcinomas (mBrCAs) are a highly aggressive subtype of triple negative breast cancer (TNBC) with histological evidence of epithelial to mesenchymal transition (EMT) and aberrant differentiation, including varied non-glandular features. CCN6/WISP3 tumor suppressor gene inactivation and b-catenin-dependent Wnt pathway activation are often seen in mBrCAs.
Read the full summary ↓
We have reported MMTV-Cre;Ccn6fl/fl (Ccn6-KO) mice develop spindle mBrCAs with EMT and elevated expression of the Wnt/b-catenin pathway genes HMGA2 and IGF2BP2. The mechanisms by which the secreted CCN6 protein exerts tumor suppressor functions in breast tissues are uncertain. Here, we show recombinant CCN6 protein interacts with Wnt receptor FZD8 and co-receptor LRP6 on mBrCA cells to antagonize Wnt ligand-mediated activation of b-catenin/T-cell-factor (TCF) transcription. We identify the gene for histone methyltransferase EZH2, the catalytic component of polycomb repressive complex 2, as a β-catenin/TCF transcriptional target in Ccn6-KO mBrCA cells. Inhibition of Wnt/β-catenin/TCF function in Ccn6-KO mBrCA cells led to reduced EZH2 levels and decreased histone H3 lysine 27 trimethylation, resulting in deregulation of specific gene targets. Pharmacological inhibition of EZH2 reduced growth and metastasis of Ccn6-KO mBrCA mammary tumors and induced an epithelial phenotype in vivo. In human breast cancer specimens, low CCN6 is significantly associated with activated β-catenin and high EZH2 in spindle mBrCAs compared to other subtypes. Collectively, our findings establish a novel tumor suppressor mechanism for CCN6 as a key negative regulator of a b-catenin/TCF-EZH2 axis and highlight how CCN6 restoration or b-catenin or EZH2 inhibition could have therapeutic relevance for patients with spindle mBrCAs.
This dataset
Open GSE250574 in finder → Find more mouse ChIP / ATAC / CUT&Tag 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 GSE250574_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1054561 and SRA study SRP479043. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
16 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 16 sample titles: 16 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
Datasets on a similar topic

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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.