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EZH2-targeted PROTACs target the EZH2/FOXM1 axis and reduce breast cancer cell growth

GSE270769 Homo sapiens (human) RNA-seq (gene expression) 38 samples Submitted 2025/05/01 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 38 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)
Topic
Breast cancerThis series is part of our curated briefing on it.
Samples
38 samples: 18 conditions, mostly in duplicateGroups 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
EZH2 PROTACs target EZH2- and FOXM1-associated oncogenic nodes, suppressing breast cancer cell growthOncogene · 2024
Summary (written by the submitters)
Breast cancer (BCa) remains the second leading cause of cancer-related mortalities in women, and acquired resistance to hormone therapies, such as tamoxifen, an estrogen receptor inhibitor, is a major hurdle in the treatment of luminal BCa. Another subtype, triple negative BCa (TNBC), is associated with aggressive disease and poor prognosis.
Read the full summary ↓
The enhancer of zeste homolog 2 (EZH2), the methyltransferase component of the polycomb repressive complex 2 (PRC2), is overexpressed in BCa and has been implicated in tamoxifen resistance. In addition to its PRC2-dependent canonical transcription repressive role through catalyzing histone 3 lysine 27 trimethylation (H3K27me3), evidence suggests that EZH2 can function noncanonically, in a methyltransferase-independent manner, as a transcription activator through interacting with hormone receptors and oncogenic transcription factors. Unlike methyltransferase inhibitors, proteolysis targeting chimeras (PROTAC), which target EZH2 and interacting proteins for degradation, can suppress both activating and repressive functions of EZH2. Previous studies have suggested that PROTACs can be leveraged to inhibit TNBC cell growth. In this study, we expand our scope to test whether EZH2 targeted PROTACs can effectively inhibit luminal BCa cell growth. We find that EZH2-targeted PROTACs, MS177 and MS8815, effectively inhibited the growth luminal BCa cells, including those with acquired tamoxifen resistance, to a much greater degree when compared to methyltransferase inhibitors. Similarly, PROTACs uniquely reduced the expression of genes involved in cell cycle progression, including forkhead box M1 (FOXM1) target genes, in BCa cell lines. Likewise, promoter regions with EZH2 binding in the absence of H3K27me3 were enriched with FOXM1 target genes in both luminal BCa and TNBC cell lines, suggesting a regulatory mechanism independent of hormone receptor status. EZH2 PROTAC treatment reduced FOXM1 protein expression and increased its degradation. In clinical samples, EZH2 mRNA expression tightly correlated with FOXM1 and FOXM1 target genes. Together, this study suggests that EZH2 targeted PROTACs represent a promising avenue of research for the future treatment of BCa, including in the setting of tamoxifen resistance.
Published in
EZH2 PROTACs target EZH2- and FOXM1-associated oncogenic nodes, suppressing breast cancer cell growth
Corbin J, Yu X, Jin J et al. · Oncogene 2024 · PMID 39112519 · doi:10.1038/s41388-024-03119-9
This dataset
Open GSE270769 in finder → Find more human RNA-seq datasets → Breast cancer landscape →
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 GSE270769_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: 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 PRJNA1128142 and SRA study SRP516102. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39112519) ↗
Study design
18 conditions, mostly in duplicate
T47DTR_DMSO ×4 T47D_DMSO ×2 T47D_MS177 ×2 T47D_MS177N1 ×2 T47D_MS177N2 ×2 T47D_C24 ×2 T47DTR_MS177 ×2 T47DTR_MS177N1 ×2 +10 more

Supports a between-group comparison across 38 samples.

How we read this: 18 replicated groups read from 38 sample titles; they account for 38 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
More Breast cancer datasets

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.