GEO series

Targeting the ERα DBD-LBD interface with mitoxantrone disrupts receptor function through proteasomal degradation

GSE303561 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2025/07/24 Platform GPL21697

At a glance

RNA-seq (gene expression) · human · 24 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: 24 samples: 12 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: Targeting the ERα DBD-LBD Interface with Mitoxantrone Disrupts Receptor Function through Proteasomal DegradationMolecular cancer therapeutics · 2026

Summary (written by the submitters)

The estrogen receptor (ER or ERα) remains the primary therapeutic target for luminal breast cancer, with current treatments centered on competitive antagonists, receptor down-regulators, and aromatase inhibitors. This therapeutic landscape frames our discovery of an alternative mechanism of ER inhibition that targets the critical interface between the DNA-binding domain (DBD) and ligand-binding domain (LBD) of the receptor.

Read the full summary ↓

We identified mitoxantrone (MTO), an FDA-approved topoisomerase II inhibitor, as a specific ligand for this previously unexplored DBD-LBD interface. Through integration of computational, biophysical, biochemical, and cellular analyses, we demonstrate that independent of its DNA damage response activity, MTO binding induces ER conformational changes, leading to cytoplasmic redistribution and proteasomal degradation. Notably, MTO also effectively inhibits constitutively active ER mutants (Y537S and D538G) commonly associated with endocrine therapy resistance, suppressing ER/ER-mutant-dependent gene expression and tumor growth more potently than fulvestrant. These findings establish the DBD-LBD interface as a crucial regulatory point for ER function, suggesting a new paradigm for targeting domain interfaces across the nuclear receptor family.

Published in

Targeting the ERα DBD-LBD Interface with Mitoxantrone Disrupts Receptor Function through Proteasomal Degradation

Wang H, Luo Y, Artham S et al. · Molecular cancer therapeutics 2026 · PMID 40931856 · doi:10.1158/1535-7163.MCT-25-0405

This dataset

Open GSE303561 in finder → Find more human RNA-seq 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 GSE303561_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 PRJNA1295824 and SRA study SRP603227. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40931856) ↗

Study design

12 conditions, mostly in duplicate

KI-Ctrl_DMSO ×2 KI-Ctrl_ICI ×2 KI-Ctrl_T4 ×2 KI-Ctrl_combination ×2 KI-537_DMSO ×2 KI-537_ICI ×2 KI-537_T4 ×2 KI-537_combination ×2 +4 more

Supports a between-group comparison across 24 samples.

How we read this: 12 replicated groups read from 24 sample titles; they account for 24 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

GSM9130726 KI-Ctrl_DMSO_rep1 KI-Ctrl_DMSO
GSM9130727 KI-Ctrl_DMSO_rep2 KI-Ctrl_DMSO
GSM9130728 KI-Ctrl_ICI_rep1 KI-Ctrl_ICI
GSM9130729 KI-Ctrl_ICI_rep2 KI-Ctrl_ICI
GSM9130730 KI-Ctrl_T4_rep1 KI-Ctrl_T4
GSM9130731 KI-Ctrl_T4_rep2 KI-Ctrl_T4
GSM9130732 KI-Ctrl_combination_rep1 KI-Ctrl_combination
GSM9130733 KI-Ctrl_combination_rep2 KI-Ctrl_combination
GSM9130734 KI-537_DMSO_rep1 KI-537_DMSO
GSM9130735 KI-537_DMSO_rep2 KI-537_DMSO
GSM9130736 KI-537_ICI_rep1 KI-537_ICI
GSM9130737 KI-537_ICI_rep2 KI-537_ICI
GSM9130738 KI-537_T4_rep1 KI-537_T4
GSM9130739 KI-537_T4_rep2 KI-537_T4
GSM9130740 KI-537_combination_rep1 KI-537_combination
GSM9130741 KI-537_combination_rep2 KI-537_combination
GSM9130742 KI-538_DMSO_rep1 KI-538_DMSO
GSM9130743 KI-538_DMSO_rep2 KI-538_DMSO
GSM9130744 KI-538_ICI_rep1 KI-538_ICI
GSM9130745 KI-538_ICI_rep2 KI-538_ICI
GSM9130746 KI-538_T4_rep1 KI-538_T4
GSM9130747 KI-538_T4_rep2 KI-538_T4
GSM9130748 KI-538_combination_rep1 KI-538_combination
GSM9130749 KI-538_combination_rep2 KI-538_combination

Datasets on a similar topic

GSE296736 Lysosomal RNA profiling reveals targeting of specific types of RNAs for degradation 99 samples shares degradation, targeting
GSE263153 Targeted Degradation of CDK9 Potently Disrupts MYC Network 91 samples shares degradation, disrupts
GSE255133 Targeting histone H2B acetylated enhanceosomes via p300/CBP degradation in prostate cancer (RNA-Seq) 32 samples shares degradation, targeting
GSE273150 Targeting USP8 Causes Synthetic Lethality through Degradation of FGFR2 in ARID1A-Deficient Ovarian Clear Cell Carcinoma 12 samples shares degradation, targeting
GSE279343 Chemically Engineered Antibodies for Autophagy-based Receptor Degradation 12 samples shares degradation, receptor
GSE322892 Novel hydrophobic tag degraders overcome endocrine-resistant breast cancer by recruiting HSP27-mediated E3 ligase complex for ERα proteasomal degradation 9 samples shares proteasomal, degradation
GSE296685 Targeting HDAC8 sensitizes tyrosine kinase inhibitors in the elimination of B-cell acute lymphoblastic leukemia cells through degradation of HIF-1α 9 samples shares degradation, targeting
GSE310746  PARG regulates the proteasomal degradation of TARG1 6 samples shares proteasomal, degradation

Search all human RNA-seq datasets in GEO →

Share this dataset

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.