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Anti-Neoplastic Activity of Estrogen Receptor Beta in Chemoresistant Triple-Negative Breast Cancer

GSE300447 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/07/01 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples
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
Anti-Neoplastic Activity of Estrogen Receptor Beta in Chemoresistant Triple-Negative Breast CancerCancers · 2025
Summary (written by the submitters)
The standard of care for triple-negative breast cancer is chemotherapy followed by surgical resection, and in most cases, additional rounds of chemotherapy treatment. While highly effective, approximately half of patients will experience disease recurrence that does not respond to additional rounds of treatment.
Read the full summary ↓
Previous findings demonstrate that estrogen receptor beta (ERb) is expressed in upwards of 20% of triple-negative tumors, and that ERb functions as a tumor suppressor in triple-negative breast cancer models, it was of interest to determine if the tumor-suppressive effects of ERb persisted in chemo-therapy-resistant forms of the disease. Here, we demonstrate that the activation of ERb in chemotherapy-resistant triple-negative breast cancer cell lines elicits equivalent or superior inhibitory effects compared to chemotherapy-sensitive counterparts. These findings support the potential use of ERb-targeting agents in advanced forms of the disease.
Published in
Anti-Neoplastic Activity of Estrogen Receptor Beta in Chemoresistant Triple-Negative Breast Cancer
Wang X, Emch MJ, Goetz MP et al. · Cancers 2025 · PMID 40647431 · doi:10.3390/cancers17132132
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 GSE300447_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 PRJNA1280979 and SRA study SRP594089. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 18 more — browse all 18 samples with per-sample file links →

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