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Estrogenic Endocrine Disrupting Compounds Increase Cell Proliferation and Cancer Stemness in Estrogen Receptor Positive Breast Cancer Cells

GSE311462 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2026/07/22 Platform GPL20301
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)
Topic
Breast cancerThis series is part of our curated briefing on it.
Samples
24 samples: 8 conditions, mostly in triplicateGroups 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
The Endocrine Disrupting Compounds Bisphenol-A and α-Zeranol Mimic the Estrogen Transcriptional Program to Promote Proliferation and Stemness in Breast Cancer CellsMolecular carcinogenesis · 2026
Summary (written by the submitters)
Estrogenic endocrine disrupting compounds (EDCs) found in plastics, drinking water, and food are able to bind to the estrogen receptor (ER). Excessive estrogen signaling drives proliferation, progression, and the formation of breast cancer stem cells (CSCs) in ER-positive breast cancer. Thus, we hypothesized that estrogenic EDCs mimic estrogen (E2) in breast cancer cell lines.
Read the full summary ↓
Three estrogenic EDCs routinely found in human biosamples were selected for analysis: bisphenol-A (BPA), diethyl-hexyl phthalate (DEHP), and alpha-zeranol (αZAL). We assessed proliferation, transcriptional reprogramming, and CSC formation in several breast cancer cell lines. E2, BPA, and αZAL significantly increased cell proliferation in ER-positive, but not in ER-negative cell lines. This was reversed with the administration of an ER-antagonist, ICI 182,780. BPA and αZAL upregulated estrogen target genes (PGR, TFF1) and increased levels of cell cycle protein. Whole-transcriptome RNA sequencing analysis revealed that BPA and αZAL altered the expression of genes in pathways related to cell division, DNA repair, and estrogen signaling, with a substantial transcriptional overlap between EDC and estrogen treatments. Additionally, in the ER-positive cell line MCF-7, BPA and αZAL increased the proportion of CSCs, defined as the CD24low/CD44high expressing subpopulation. Overall, these data indicate that BPA and αZAL act as functional estrogen mimics in breast cancer cells, activating canonical estrogen signaling pathways and promoting stem-like characteristics. Exposure to EDCs is nearly unavoidable; therefore, understanding their estrogenic activities is crucial for assessing environmental contributions to breast cancer risk. This work provides mechanistic insight into how environmental EDCs may influence ER-positive breast cancer biology.
Published in
The Endocrine Disrupting Compounds Bisphenol-A and α-Zeranol Mimic the Estrogen Transcriptional Program to Promote Proliferation and Stemness in Breast Cancer Cells
Winz C, Li E, Xie C et al. · Molecular carcinogenesis 2026 · PMID 42070278 · doi:10.1002/mc.70127
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 GSE311462_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 PRJNA1369499 and SRA study SRP648940. Searching any of these in the dataset finder brings you back here.

Study design
8 conditions, mostly in triplicate
MCF7 control 12 hours ×3 MCF7 control 72 hours ×3 MCF7 E2 12 hours ×3 MCF7 E2 72 hours ×3 MCF7 BPA 12 hours ×3 MCF7 BPA 72 hours ×3 MCF7 aZAL 12 hours ×3 MCF7 aZAL 72 hours ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 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
More Breast cancer datasets

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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.